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# Shown as the "Sponsor" button on the GitHub repo
github: otherworld-dev
custom:
- "https://www.paypal.com/donate/?hosted_button_id=MA56N6K8FSTQ2"

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# Python
__pycache__/
*.pyc
# Claude Code
.claude/
CLAUDE.md
.claudeignore
# Build artifacts
*.egg-info/
build/
dist/
# KUKA proprietary material - never commit (copyright)
KUKA.RobotSensorInterface*.pdf
TestServer.exe

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cff-version: 1.2.0
message: "If you use this software, please cite it as below."
type: software
title: "RSIPI: Robot Sensor Interface for Python"
authors:
- family-names: Morgan
given-names: Adam
email: contact@otherworld.dev
affiliation: Swansea University
version: 0.1.1
date-released: 2026-07-11
url: "https://github.com/otherworld-dev/rsi-pi"
repository-code: "https://github.com/otherworld-dev/rsi-pi"
license: Apache-2.0
keywords:
- KUKA
- robotics
- RSI
- real-time control
- industrial robots

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# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## What This Project Does
RSIPI enables real-time control of KUKA industrial robots from Python via the RSI (Robot Sensor Interface) protocol. The robot sends its position ~250 times/second over UDP, and this library lets you send back position corrections to control the robot externally.
## Build & Development Commands
```bash
# Install dependencies
pip install -e .
# Or install from requirements (if present)
pip install pandas>=2.0 numpy>=1.22 matplotlib>=3.5 lxml>=4.9 scipy>=1.8
# Run the CLI
python -m RSIPI.rsi_cli --config RSI_EthernetConfig.xml
# Run the echo server (for offline testing without a real robot)
python -m RSIPI.rsi_echo_server
```
**No test suite exists** - testing is done via the echo server simulation and example scripts in `examples/`.
## Architecture
### Core Communication Flow
```
KUKA Robot Controller <--UDP/XML--> NetworkProcess <--multiprocessing.Manager--> RSIClient <-- RSIAPI/CLI
```
1. **NetworkProcess** (`network_handler.py`) - Runs in separate process via `multiprocessing.Process`. Binds to UDP socket, receives XML from robot, parses into `receive_variables`, sends XML from `send_variables` back to robot. Uses `start_event` to wait for explicit start signal.
2. **RSIClient** (`rsi_client.py`) - Orchestrates the system. Initializes ConfigParser, SafetyManager, and NetworkProcess. Uses `multiprocessing.Manager` dicts for thread-safe variable sharing between processes.
3. **RSIAPI** (`rsi_api.py`) - High-level API wrapping RSIClient. Runs RSIClient in a daemon thread. Provides trajectory planning, logging, plotting, and safety controls.
4. **RSICommandLineInterface** (`rsi_cli.py`) - Interactive CLI that wraps RSIAPI.
### Key Shared State
Variables are shared between processes using `multiprocessing.Manager().dict()`:
- `send_variables` - Values to send to robot (RKorr corrections, digital outputs, etc.)
- `receive_variables` - Values received from robot (RIst position, ASPos joints, IPOC timestamp)
### Configuration
`RSI_EthernetConfig.xml` defines:
- Network settings (IP, port) in `<CONFIG>` section
- Send variables in `<SEND><ELEMENTS>` - what the robot receives from us
- Receive variables in `<RECEIVE><ELEMENTS>` - what we receive from robot
Variable tags like `DEF_RIst` get the `DEF_` prefix stripped and are expanded using `internal_structure` in ConfigParser to full dicts (e.g., `RIst: {X, Y, Z, A, B, C}`).
### Safety Layer
**SafetyManager** (`safety_manager.py`) validates all outgoing values against configurable limits. Can load limits from `.rsi.xml` files. Supports emergency stop and safety override modes.
### Trajectory Execution
`TrajectoryPlanner` generates interpolated waypoints. `execute_trajectory()` in RSIAPI uses asyncio to send points at specified rate (default 12ms for Cartesian, 400ms for joints).
## Important Patterns
- **IPOC synchronization**: The robot sends an IPOC (timestamp) value. The response must include `IPOC + 4` to maintain sync. This is handled automatically in `NetworkProcess.process_received_data()`.
- **Lazy client initialization**: RSIAPI uses `_ensure_client()` pattern - RSIClient is created on first use, not at RSIAPI instantiation.
- **Non-blocking start**: `start_rsi()` runs the client loop in a daemon thread. The NetworkProcess waits on `start_event` before binding the socket.
## File Locations
- Source code: `src/RSIPI/`
- Example scripts: `examples/`
- Config template: `RSI_EthernetConfig.xml`
- Logs written to: `logs/` (created at runtime)

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499
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@ -1,499 +0,0 @@
# Phase 2: Network Reliability - Complete
## Summary
Successfully implemented comprehensive network reliability infrastructure for RSIPI. The library now provides real-time performance monitoring, automatic connection recovery, and long-duration stability testing capabilities - essential for industrial robot control applications requiring 24/7 operation.
## What Changed
### Network Monitoring and Diagnostics
The RSIPI library now tracks detailed timing and network quality metrics in real-time:
1. **Timing Instrumentation** - Records cycle time, jitter, and latency with minimal overhead
2. **IPOC Gap Detection** - Identifies missed packets via IPOC sequence analysis
3. **Packet Loss Tracking** - Monitors communication reliability with percentage metrics
4. **Watchdog Timer** - Detects communication timeouts (>1 second without packets)
5. **Health Monitoring** - Real-time health status with threshold-based warnings
### Automatic Reconnection
New auto-reconnection manager provides graceful recovery from network failures:
1. **Background Monitoring** - Checks watchdog status every 2 seconds
2. **Configurable Retry Strategies**:
- IMMEDIATE: Reconnect without delay
- LINEAR_BACKOFF: Incremental retry delays (5s, 10s, 15s, ...)
- EXPONENTIAL_BACKOFF: Exponential retry delays (5s, 10s, 20s, 40s, ...)
3. **Connection Verification** - Validates successful reconnection with health checks
4. **Statistics Tracking** - Records reconnection attempts, failures, and timestamps
5. **Event Callbacks** - Optional callbacks for reconnection success/failure
### Long-Duration Testing
24-hour stability test infrastructure for validating production-readiness:
1. **Configurable Duration** - Run tests from minutes to days
2. **Sample Collection** - Records metrics at configurable intervals (default: 60s)
3. **Real-Time Logging** - Progress updates with health status and warnings
4. **JSON Reports** - Comprehensive statistical analysis of test results
5. **Graceful Interruption** - Handles KeyboardInterrupt, always generates report
## New Files Created
```
rsi-pi/
├── src/RSIPI/
│ ├── timing_metrics.py # NEW (305 lines)
│ │ ├── TimingMetrics class
│ │ │ ├── record_cycle() - Records IPOC and cycle time
│ │ │ ├── check_watchdog() - Detects communication timeout
│ │ │ ├── get_current_stats() - Real-time statistics
│ │ │ ├── get_detailed_stats() - Statistics with percentiles
│ │ │ └── get_health_status() - Health check with warnings
│ │ └── NetworkQualityMonitor class
│ │ ├── is_healthy() - Overall health status
│ │ ├── get_warnings() - Active warning messages
│ │ └── get_quality_score() - 0-100 quality score
│ │
│ └── auto_reconnect.py # NEW (241 lines)
│ ├── ReconnectStrategy enum
│ │ ├── IMMEDIATE
│ │ ├── LINEAR_BACKOFF
│ │ └── EXPONENTIAL_BACKOFF
│ └── AutoReconnectManager class
│ ├── start() - Start background monitoring
│ ├── stop() - Stop background monitoring
│ ├── _monitor_loop() - Watchdog monitoring thread
│ ├── _attempt_reconnection() - Retry logic with backoff
│ └── _verify_connection() - Post-reconnect validation
│
└── tests/
└── stability_test.py # NEW (365 lines)
├── StabilityTest class
│ ├── setup() - Initialize API with auto-reconnect
│ ├── run() - Execute test with sample collection
│ ├── _collect_sample() - Get metrics snapshot
│ ├── _log_progress() - Real-time progress logging
│ ├── _cleanup() - Stop API and generate report
│ ├── _generate_report() - Statistical analysis
│ └── _print_summary() - Human-readable summary
└── main() - Command-line interface
```
## Modified Files
### [src/RSIPI/network_handler.py](rsi-pi/src/RSIPI/network_handler.py)
**Integration of timing metrics into real-time UDP loop:**
- Added `TimingMetrics` initialization in `run()` method
- Record cycle on every received packet with `record_cycle(ipoc)`
- Batch updates to shared metrics dict every 100 cycles (~400ms)
- Zero-overhead design preserves 250Hz real-time performance
**Key Changes:**
```python
# Added to __init__
def __init__(self, ..., metrics_dict: Optional[Any] = None):
self.metrics_dict = metrics_dict
# In run() method
if self.metrics_dict is not None:
self.timing_metrics = TimingMetrics()
# In _run_loop()
if self.timing_metrics is not None:
ipoc = self.receive_variables.get("IPOC", 0)
self.timing_metrics.record_cycle(ipoc)
update_counter += 1
if update_counter >= 100:
self._update_metrics_dict()
update_counter = 0
```
### [src/RSIPI/rsi_client.py](rsi-pi/src/RSIPI/rsi_client.py)
**Added auto-reconnection support and shared metrics dictionary:**
- Created `Manager().dict()` for inter-process metrics sharing
- Pass metrics dict to NetworkProcess constructor
- New constructor parameters for auto-reconnection configuration
- Start/stop auto-reconnect monitor in lifecycle methods
**Key Changes:**
```python
# Added imports
from .auto_reconnect import AutoReconnectManager, ReconnectStrategy
# New constructor parameters
def __init__(
self,
config_file: str,
rsi_limits_file: Optional[str] = None,
enable_auto_reconnect: bool = False,
auto_reconnect_retries: int = 5,
auto_reconnect_delay: float = 5.0
) -> None:
# Created shared metrics dict
self.metrics_dict = self.manager.dict()
# Pass to NetworkProcess
self.network_process = NetworkProcess(..., self.metrics_dict)
# Initialize auto-reconnect manager
if enable_auto_reconnect:
self.auto_reconnect_manager = AutoReconnectManager(
client=self,
enabled=True,
max_retries=auto_reconnect_retries,
retry_delay=auto_reconnect_delay,
strategy=ReconnectStrategy.LINEAR_BACKOFF
)
# In start() method
if self.auto_reconnect_manager:
self.auto_reconnect_manager.start()
# In stop() method
if self.auto_reconnect_manager:
self.auto_reconnect_manager.stop()
```
### [src/RSIPI/diagnostics_api.py](rsi-pi/src/RSIPI/diagnostics_api.py)
**Fully implemented DiagnosticsAPI (was placeholder in Phase 5):**
- `get_stats()` - Comprehensive network and performance statistics
- `get_timing()` - Timing-specific metrics (cycle time, jitter)
- `get_network_quality()` - Network quality metrics (packet loss, IPOC gaps)
- `is_healthy()` - Overall system health check
- `get_warnings()` - Active warning messages
- `check_watchdog()` - Watchdog timeout status
- `format_stats()` - Human-readable statistics output
## Example Usage
### Basic Diagnostics
```python
from RSIPI import RSIAPI
api = RSIAPI('RSI_EthernetConfig.xml')
api.start()
# Check overall health
if api.diagnostics.is_healthy():
print("✅ Network healthy")
else:
print("⚠️ Network issues detected")
for warning in api.diagnostics.get_warnings():
print(f" - {warning}")
# Get timing metrics
timing = api.diagnostics.get_timing()
print(f"Mean cycle time: {timing['mean_cycle_time']*1000:.2f}ms")
print(f"Jitter: {timing['jitter']*1000:.2f}ms")
# Get network quality
network = api.diagnostics.get_network_quality()
print(f"Packet loss: {network['packet_loss_rate']:.2f}%")
print(f"IPOC gaps per 1000 cycles: {network['ipoc_gap_rate']:.1f}")
# Print formatted statistics
print(api.diagnostics.format_stats())
api.stop()
```
### Auto-Reconnection
```python
from RSIPI import RSIAPI
# Enable auto-reconnection with unlimited retries
api = RSIAPI(
'RSI_EthernetConfig.xml',
enable_auto_reconnect=True,
auto_reconnect_retries=0, # 0 = unlimited
auto_reconnect_delay=10.0 # 10 second initial delay
)
api.start()
# Auto-reconnection will now handle any communication failures
# Monitor will check watchdog every 2 seconds
# Will attempt reconnection with linear backoff (10s, 20s, 30s, ...)
# Your application code here...
api.stop() # Stops auto-reconnect monitor gracefully
```
### Custom Reconnection Callbacks
```python
from RSIPI import RSIAPI
from RSIPI.auto_reconnect import ReconnectStrategy
def on_reconnect_success():
print("✅ Reconnected successfully!")
# Re-initialize application state, restart trajectories, etc.
def on_reconnect_failure():
print("❌ Reconnection failed after max retries")
# Send alert, log failure, initiate shutdown, etc.
api = RSIAPI('RSI_EthernetConfig.xml')
api.start()
# Manually configure auto-reconnect with callbacks
from RSIPI.auto_reconnect import AutoReconnectManager
api.auto_reconnect_manager = AutoReconnectManager(
client=api,
enabled=True,
max_retries=10,
retry_delay=5.0,
strategy=ReconnectStrategy.EXPONENTIAL_BACKOFF,
on_reconnect=on_reconnect_success,
on_failure=on_reconnect_failure
)
api.auto_reconnect_manager.start()
# Your application code here...
api.auto_reconnect_manager.stop()
api.stop()
```
### Running Stability Test
**Quick 5-minute test:**
```bash
cd tests
python stability_test.py --duration 0.083 --interval 10
```
**1-hour test with custom config:**
```bash
python stability_test.py \
--duration 1 \
--config custom_config.xml \
--interval 30 \
--output results_1hr.json
```
**Full 24-hour test:**
```bash
python stability_test.py \
--duration 24 \
--interval 60 \
--output stability_24hr.json
```
**Example output:**
```
=== RSI Stability Test ===
Config: RSI_EthernetConfig.xml
Duration: 1.0 hours
Check interval: 30.0s
Output: stability_test_20260117_103045.json
==================================================
Starting RSI communication...
✅ RSI communication started successfully
Test started at 2026-01-17 10:30:45
Will run until 2026-01-17 11:30:45
✅ Progress: 8.3% | Elapsed: 0.08h | Remaining: 0.92h | Samples: 6 | Jitter: 0.45ms | Loss: 0.00%
✅ Progress: 16.7% | Elapsed: 0.17h | Remaining: 0.83h | Samples: 12 | Jitter: 0.52ms | Loss: 0.00%
...
✅ Progress: 100.0% | Elapsed: 1.00h | Remaining: 0.00h | Samples: 120 | Jitter: 0.48ms | Loss: 0.01%
=== Test Complete ===
Stopping RSI communication...
Generating report...
✅ Report saved to: stability_test_20260117_103045.json
============================================================
STABILITY TEST SUMMARY
============================================================
Test Duration: 1.00 hours
Total Samples: 120
Health: 100.0% healthy
Healthy samples: 120
Unhealthy samples: 0
Timing Performance:
Mean cycle time: 4.12ms
Cycle time range: 3.85 - 4.42ms
Mean jitter: 0.48ms
Max jitter: 0.85ms
Network Quality:
Mean packet loss: 0.008%
Max packet loss: 0.040%
Overall Result: ✅ PASS
============================================================
```
## Metrics Tracked
### Timing Metrics
| Metric | Description | Units |
|--------|-------------|-------|
| `mean_cycle_time` | Average time between packets | seconds |
| `std_cycle_time` | Standard deviation of cycle time | seconds |
| `min_cycle_time` | Minimum cycle time observed | seconds |
| `max_cycle_time` | Maximum cycle time observed | seconds |
| `jitter` | Cycle time variance (std_dev) | seconds |
### Network Quality Metrics
| Metric | Description | Units |
|--------|-------------|-------|
| `packet_loss_rate` | Percentage of packets lost | percent |
| `ipoc_gap_rate` | IPOC gaps per 1000 cycles | gaps/1000 cycles |
| `total_cycles` | Total communication cycles | count |
| `total_packets_lost` | Total packets lost | count |
| `total_ipoc_gaps` | Total IPOC discontinuities | count |
### Health Indicators
| Indicator | Threshold | Description |
|-----------|-----------|-------------|
| `is_healthy` | All checks pass | Overall system health |
| `watchdog_timeout` | >1 second | Communication timeout detected |
| High jitter | >2ms | Excessive timing variance |
| High packet loss | >1% | Network reliability issue |
| High cycle time | >6ms (1.5x expected) | Performance degradation |
## Health Thresholds
The system is considered **healthy** when:
- No watchdog timeout (packets received within last 1 second)
- Jitter < 2ms (timing variance acceptable)
- Packet loss < 1% (minimal data loss)
- Mean cycle time < 6ms (within 1.5x expected 4ms)
Violations of any threshold trigger:
- Warning messages in log
- `is_healthy()` returns False
- Warning list populated with specific issues
## Performance Impact
**Timing Metrics Collection:**
- Per-cycle overhead: ~10 microseconds (timestamp + IPOC append)
- Shared dict update: Every 100 cycles (~400ms) to minimize overhead
- Total impact: <0.1% on 250Hz real-time loop
- No GIL contention (metrics calculated in NetworkProcess)
**Auto-Reconnection Monitoring:**
- Background thread sleeps 2 seconds between checks
- Reconnection attempt: ~3-5 seconds (stop, wait, start, verify)
- Zero impact during normal operation (thread sleeping)
## Architecture Details
### Multiprocessing Design
```
Main Process (RSIAPI)
├── Manager.dict() (shared metrics_dict)
├── RSIClient
│ ├── AutoReconnectManager (if enabled)
│ │ └── Background Thread (monitors watchdog every 2s)
│ └── NetworkProcess (separate process)
│ ├── TimingMetrics
│ │ ├── Records IPOC + timestamp each cycle
│ │ └── Updates shared dict every 100 cycles
│ └── UDP Communication Loop (250Hz)
└── DiagnosticsAPI
└── Reads from shared metrics_dict
```
**Key Design Decisions:**
1. **Separate Process for Network**: Avoids Python GIL, guarantees real-time performance
2. **Shared Manager.dict()**: Inter-process communication for metrics
3. **Batched Updates**: Only update shared dict every 100 cycles to minimize overhead
4. **Deferred Statistics**: Heavy calculations (mean, stdev) done on-demand, not per-cycle
## Migration Notes
### No Breaking Changes
Phase 2 is **fully backward compatible** with Phase 1 & 5 API:
- All existing code continues to work without modification
- Auto-reconnection is opt-in via constructor parameter
- DiagnosticsAPI methods are new additions (no conflicts)
### Opt-In Auto-Reconnection
```python
# Old code (still works, no auto-reconnect)
api = RSIAPI('RSI_EthernetConfig.xml')
# New code (with auto-reconnect)
api = RSIAPI(
'RSI_EthernetConfig.xml',
enable_auto_reconnect=True,
auto_reconnect_retries=0, # unlimited
auto_reconnect_delay=5.0
)
```
## Benefits of Phase 2
1. **Production-Ready Reliability**: Automatic recovery from network failures
2. **Real-Time Diagnostics**: Comprehensive metrics without performance impact
3. **Early Warning System**: Detect network degradation before failures occur
4. **Validation Infrastructure**: 24-hour stability testing for production deployments
5. **Research Quality**: Publication-ready performance metrics and analysis
## Phase 2 Status: ✅ COMPLETE
All planned features have been implemented:
- ✅ Timing instrumentation (latency, jitter, cycle time tracking)
- ✅ Watchdog timer for communication loss detection
- ✅ Network quality monitoring (packet loss, IPOC gaps)
- ✅ CSV logging optimization (batched updates)
- ✅ Auto-reconnection with graceful recovery
- ✅ 24-hour stability test infrastructure
## Next Steps
### Immediate Actions
1. Run actual 24-hour stability test with real robot hardware
2. Collect performance metrics for publication
3. Document any issues discovered during long-duration testing
### Phase 3: KRL Coordination (Upcoming)
- High-level Digital I/O API (set_output, get_input, pulse)
- KRL state coordination helpers (wait_for_signal, signal_complete)
- Parameter passing via Tech variables
- KRL code templates for coordination scenarios
- Enhanced inject_rsi_to_krl with coordination boilerplate
The `api.io` and `api.krl` namespaces will be enhanced with Python-KRL coordination features to enable seamless bidirectional communication between RSIPI and KRL programs.
## Commits
- `6e8ea2e` - Implement Phase 2: Network Reliability and Diagnostics (January 17, 2026)
- Created timing_metrics.py with TimingMetrics and NetworkQualityMonitor
- Integrated metrics into network_handler.py real-time loop
- Updated rsi_client.py with shared metrics dictionary
- Fully implemented diagnostics_api.py
- `bb65500` - Complete Phase 2: Auto-reconnection and stability testing (January 17, 2026)
- Created auto_reconnect.py with AutoReconnectManager
- Integrated auto-reconnect into rsi_client.py
- Created tests/stability_test.py for long-duration testing
- `edca436` - Update ROADMAP: Mark Phase 2 as complete (January 17, 2026)
- Updated roadmap status, timeline, and success criteria

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@ -1,761 +0,0 @@
# Phase 4: Advanced Motion Control - Implementation Summary
**Date**: January 17, 2026
**Phase**: 4 of 6
**Status**: ✅ Complete
---
## Overview
Phase 4 adds professional-grade motion planning capabilities to RSIPI, enabling industrial applications requiring complex trajectories, optimized timing, and flexible coordinate systems. This phase focuses on trajectory generation, velocity profiling, geometric primitives, path blending, and coordinate transformations.
## What Was Implemented
### 1. Velocity Profiling
**File**: `src/RSIPI/motion_api.py`
**New Method**: `generate_velocity_profile()`
Generate time-optimal velocity profiles for trajectory execution with configurable acceleration limits.
```python
profiled_trajectory = api.motion.generate_velocity_profile(
trajectory=waypoints,
max_velocity=200.0, # mm/s
max_acceleration=500.0, # mm/s²
profile='trapezoidal' # or 's-curve'
)
# Returns: List[Tuple[Dict[str, float], float]]
# Each element: (waypoint, time_delta)
```
**Features**:
- **Trapezoidal Profile**: Bang-bang acceleration with constant velocity cruise phase
- Fast point-to-point motion
- Time-optimal for given velocity/acceleration limits
- Suitable for pick-and-place, navigation
- **S-Curve Profile**: Jerk-limited smooth acceleration transitions
- Reduced mechanical stress and vibration
- Smooth motion for delicate operations
- Better for assembly, inspection, coating
**Implementation**:
- Calculates Euclidean distances between waypoints
- Determines acceleration, constant velocity, and deceleration phases
- Handles both full trapezoidal and triangular (short distance) profiles
- S-curve uses sine function for smooth jerk limiting
- Returns trajectory with precise timing for each waypoint
---
### 2. Geometric Motion Primitives
**File**: `src/RSIPI/motion_api.py`
#### 2.1 Arc Generation
**New Method**: `generate_arc()`
Generate circular arc trajectories in specified planes.
```python
arc = api.motion.generate_arc(
center={"X": 100, "Y": 0, "Z": 500},
radius=50.0,
start_angle=0, # degrees
end_angle=90, # degrees
steps=50,
plane='XY' # or 'XZ', 'YZ'
)
```
**Features**:
- Partial circular arcs (any start/end angle)
- Multiple plane support (XY, XZ, YZ)
- Preserves orientation (A, B, C) from center point
- Configurable point density
**Use Cases**:
- Curved approach paths
- Obstacle avoidance
- Rounded corners in machining
- Smooth insertion trajectories
#### 2.2 Circle Generation
**New Method**: `generate_circle()`
Generate complete 360° circular trajectories.
```python
circle = api.motion.generate_circle(
center={"X": 100, "Y": 0, "Z": 500},
radius=30.0,
steps=100,
plane='XY'
)
```
**Features**:
- Full circle trajectory (0° to 360°)
- Automatically closes loop
- Same plane support as arcs
- Optimized for continuous motion
**Use Cases**:
- Circular scanning/inspection
- Screw driving patterns
- Bore polishing
- Circular welds
#### 2.3 Spiral Generation
**New Method**: `generate_spiral()`
Generate expanding or contracting spiral trajectories with configurable pitch.
```python
# Expanding spiral (drilling)
spiral_expand = api.motion.generate_spiral(
center={"X": 100, "Y": 0, "Z": 500},
start_radius=5.0,
end_radius=40.0,
pitch=10.0, # mm per revolution (positive = descending)
revolutions=3.0,
steps=150,
plane='XY',
axis='Z'
)
# Contracting spiral (retraction)
spiral_contract = api.motion.generate_spiral(
center={"X": 100, "Y": 0, "Z": 470},
start_radius=40.0,
end_radius=5.0,
pitch=-10.0, # negative = ascending
revolutions=3.0,
steps=150,
plane='XY',
axis='Z'
)
```
**Features**:
- Variable radius (expanding or contracting)
- Configurable pitch (positive/negative for descending/ascending)
- Multiple plane and axis combinations
- Continuous motion from start to end
**Use Cases**:
- **Expanding**: Hole drilling, pocket milling, large hole boring
- **Contracting**: Tool retraction from deep holes, spiral unwinding
- **Constant radius + pitch**: Thread cutting, helical scanning
- **Variable radius + no pitch**: Spiral inspection patterns
---
### 3. Path Blending
**File**: `src/RSIPI/motion_api.py`
**New Method**: `blend_trajectories()`
Create smooth transitions between trajectories using cubic Hermite spline interpolation.
```python
traj1 = api.motion.generate_trajectory(p0, p1, steps=50)
traj2 = api.motion.generate_trajectory(p1, p2, steps=50)
blended = api.motion.blend_trajectories(
traj1=traj1,
traj2=traj2,
blend_radius=20.0, # Start blending 20mm before corner
blend_steps=20 # Interpolation points in blend zone
)
```
**Features**:
- Cubic interpolation for smooth velocity transitions
- Configurable blend zone radius
- Handles position and orientation blending
- Eliminates stop-and-go at trajectory junctions
**Implementation**:
- Automatically finds blend points based on radius
- Uses cubic Hermite spline with zero endpoint velocities
- Interpolates all axes (X, Y, Z, A, B, C, A1-A6)
- Preserves trajectory before/after blend zones
**Benefits**:
- **Reduced cycle time**: Eliminates stops at corners
- **Better quality**: No witness marks in welding/machining
- **Mechanical benefits**: Lower stress, reduced vibration
- **Consistent process**: Constant velocity through transitions
---
### 4. Coordinate Frame Transformations
**File**: `src/RSIPI/motion_api.py`
**New Method**: `transform_coordinates()`
Transform poses between different coordinate frames with configurable offsets.
```python
work_offset = {
"X": 500.0,
"Y": -200.0,
"Z": 50.0,
"A": 0.0,
"B": 0.0,
"C": 15.0
}
pose_base = api.motion.transform_coordinates(
pose={"X": 100, "Y": 50, "Z": 30},
from_frame='WORK',
to_frame='BASE',
frame_offset=work_offset
)
```
**Supported Frames**:
- `'BASE'`: Robot base coordinate system
- `'WORLD'`: Global world coordinates
- `'TOOL'`: Tool center point (TCP)
- `'WORK'`: Work object (pallet/fixture)
- `'ROBROOT'`: Robot root system
**Features**:
- Position transformation (X, Y, Z)
- Orientation transformation (A, B, C)
- Joint angle transformation (A1-A6)
- Simple translational and rotational offsets
**Use Cases**:
- **Multiple work objects**: Teach once, execute anywhere by changing offset
- **Tool changes**: Adapt taught positions for different tool lengths
- **Vision integration**: Apply sensor corrections to taught trajectories
- **Multi-robot cells**: Coordinate motion in shared workspace
---
## Examples Created
All examples are production-ready with comprehensive logging, error handling, and argparse CLI.
### 01_velocity_profiles.py (234 lines)
Demonstrates trapezoidal vs S-curve velocity profiling.
**Key Examples**:
- Trapezoidal profile for fast point-to-point motion
- S-curve profile for smooth motion
- Velocity sampling at different trajectory points
- Comparison of motion characteristics
**Run**: `python 01_velocity_profiles.py --config RSI_EthernetConfig.xml`
---
### 02_geometric_primitives.py (225 lines)
Demonstrates arc, circle, and spiral generation.
**Key Examples**:
1. Circular arc (90°)
2. Full circle (360°)
3. Expanding spiral (drilling pattern)
4. Contracting spiral (retraction pattern)
5. Circles in different planes (XY, XZ, YZ)
**Run**: `python 02_geometric_primitives.py --config RSI_EthernetConfig.xml`
---
### 03_path_blending.py (253 lines)
Demonstrates smooth trajectory transitions.
**Key Examples**:
1. Sharp corner vs blended corner comparison
2. Continuous path with multiple blends (square pattern)
3. Different blend radii effects
4. Blending with orientation changes
**Run**: `python 03_path_blending.py --config RSI_EthernetConfig.xml`
---
### 04_coordinate_transforms.py (284 lines)
Demonstrates coordinate frame transformations.
**Key Examples**:
1. BASE to WORLD transformation
2. TOOL frame offset (TCP calibration)
3. Transforming entire trajectories
4. Work object (pallet) transformation
5. Sensor-guided motion with corrections
**Run**: `python 04_coordinate_transforms.py --config RSI_EthernetConfig.xml`
---
### 05_combined_motion.py (336 lines)
Complete production application combining all Phase 4 features.
**Application**: Automated drilling and inspection workflow
**Flow**:
1. Navigate to inspection position (blended, S-curve, 300mm/s)
2. Spiral inspection pattern (S-curve, 50mm/s)
3. Navigate to drilling position (blended, trapezoidal, 250mm/s)
4. Expanding spiral drilling (S-curve, 30mm/s, descending)
5. Return to home (blended, trapezoidal, 350mm/s)
**Features Used**:
- ✅ Coordinate transformations (work object & tool)
- ✅ Path blending (smooth navigation)
- ✅ Velocity profiling (optimized speeds)
- ✅ Geometric primitives (spiral patterns)
**Run**: `python 05_combined_motion.py --config RSI_EthernetConfig.xml`
---
### README.md (584 lines)
Comprehensive documentation for advanced_motion examples.
**Sections**:
- Prerequisites and setup
- Example descriptions and usage
- API reference with code examples
- Customization guide
- Troubleshooting
- Advanced usage patterns
- Performance optimization tips
---
## Technical Implementation Details
### Helper Functions Added
**File**: `src/RSIPI/motion_api.py`
```python
def _calculate_distance(p1: Dict[str, float], p2: Dict[str, float]) -> float:
"""Calculate Euclidean distance between waypoints."""
# Handles X, Y, Z, A1-A6 coordinates
def _trapezoidal_profile(distances, total_distance, max_velocity, max_acceleration):
"""Generate trapezoidal velocity profile."""
# Accelerate → constant → decelerate
# Handles both full trapezoidal and triangular profiles
def _s_curve_profile(distances, total_distance, max_velocity, max_acceleration):
"""Generate S-curve velocity profile."""
# Smooth jerk-limited acceleration using sine function
def _find_blend_point(trajectory, blend_radius, from_end=False) -> int:
"""Find trajectory index at specified distance from start/end."""
# Used to locate blend zone boundaries
def _cubic_blend(p1, p2, steps) -> List[Dict[str, float]]:
"""Generate cubic Hermite spline interpolation."""
# Smooth transition with zero velocity at endpoints
```
---
## Code Quality
### Imports Added
```python
import math
import numpy as np
from typing import Dict, List, Any, Optional, Tuple, TYPE_CHECKING
```
### Documentation
- All new methods have comprehensive docstrings
- Detailed parameter descriptions
- Return value specifications
- Usage examples in docstrings
- Real-world application scenarios
### Error Handling
- Validates input parameters
- Checks for divide-by-zero conditions
- Handles edge cases (short trajectories, zero radius, etc.)
- Provides meaningful error messages
---
## Files Modified
### src/RSIPI/motion_api.py
- **Lines added**: ~550
- **New methods**: 5 public static methods
- **New helpers**: 4 private helper functions
- **Documentation**: Comprehensive docstrings for all new methods
---
## Files Created
### examples/advanced_motion/
- `01_velocity_profiles.py` (234 lines)
- `02_geometric_primitives.py` (225 lines)
- `03_path_blending.py` (253 lines)
- `04_coordinate_transforms.py` (284 lines)
- `05_combined_motion.py` (336 lines)
- `README.md` (584 lines)
**Total**: 1,916 lines of examples and documentation
---
## Usage Patterns
### Basic Velocity Profiling
```python
# Generate trajectory
trajectory = api.motion.generate_trajectory(p0, p1, steps=100)
# Apply velocity profile
profiled = api.motion.generate_velocity_profile(
trajectory,
max_velocity=200.0,
max_acceleration=500.0,
profile='s-curve'
)
# Execute with precise timing
for waypoint, dt in profiled:
api.motion.update_cartesian(**waypoint)
time.sleep(dt)
```
### Geometric Primitives
```python
# Generate drilling pattern
spiral = api.motion.generate_spiral(
center={"X": 100, "Y": 0, "Z": 500},
start_radius=5.0,
end_radius=40.0,
pitch=10.0,
revolutions=3.0,
steps=150,
plane='XY',
axis='Z'
)
# Execute
api.motion.execute_trajectory(spiral, space='cartesian', rate=0.02)
```
### Path Blending
```python
# Generate segments
seg1 = api.motion.generate_trajectory(p0, p1, steps=50)
seg2 = api.motion.generate_trajectory(p1, p2, steps=50)
# Blend for smooth transition
blended = api.motion.blend_trajectories(
seg1, seg2,
blend_radius=20.0,
blend_steps=20
)
# Execute continuous motion
api.motion.execute_trajectory(blended, space='cartesian', rate=0.02)
```
### Coordinate Transformations
```python
# Define work object offset
pallet_offset = {
"X": 800.0,
"Y": -300.0,
"Z": 50.0,
"A": 0.0,
"B": 0.0,
"C": 30.0
}
# Transform position
pick_point_pallet = {"X": 50, "Y": 50, "Z": 20}
pick_point_base = api.motion.transform_coordinates(
pick_point_pallet,
from_frame='WORK',
to_frame='BASE',
frame_offset=pallet_offset
)
```
---
## Production Applications
### Drilling and Milling
- Expanding spirals for hole boring and pocket milling
- Optimized feed rates with velocity profiling
- Smooth retractions with contracting spirals
### Assembly
- Circular insertion paths with clearance
- Smooth approach trajectories with blending
- Flexible part placement with coordinate transforms
### Inspection
- Spiral scanning patterns for large areas
- Circular scanning of features
- Consistent scanning speed with velocity profiling
### Welding and Coating
- Continuous beads at corners (no stop marks)
- Consistent deposition rate with velocity control
- Smooth transitions between weld segments
### Pick and Place
- Reduced cycle time with blended paths
- Optimized acceleration profiles
- Multiple work objects with coordinate transforms
---
## Performance Characteristics
### Trajectory Generation Speed
- **Arcs/Circles**: O(n) where n = steps
- **Spirals**: O(n) where n = steps
- **Blending**: O(n₁ + n₂) where n₁, n₂ = trajectory lengths
- **Transforms**: O(1) per point
### Memory Usage
- Trajectories stored as list of dictionaries
- Memory scales linearly with number of waypoints
- Typical trajectory (100 waypoints): ~10KB
### Real-Time Performance
- Coordinate transforms: <0.1ms per point
- Velocity profiling: <10ms for 100-point trajectory
- Path blending: <50ms for typical blend zone
- Suitable for offline trajectory generation
---
## Integration with Existing RSIPI
Phase 4 methods integrate seamlessly with existing RSIPI functionality:
```python
# Generate complex trajectory with Phase 4
trajectory = api.motion.generate_circle(...)
# Apply velocity profile (Phase 4)
profiled = api.motion.generate_velocity_profile(trajectory, ...)
# Execute with existing Phase 1-3 methods
for waypoint, dt in profiled:
api.motion.update_cartesian(**waypoint) # Phase 1
time.sleep(dt)
# Or use convenience method
api.motion.execute_trajectory(trajectory, ...) # Phase 2
```
---
## Testing and Validation
### Manual Testing
- All examples tested with simulated robot controller
- Trajectory generation verified for correctness
- Velocity profiles validated against kinematic limits
- Coordinate transforms checked with known test cases
### Edge Cases Handled
- Zero radius circles/spirals
- Zero blend radius
- Very short trajectories
- Single-point trajectories
- Identical start/end points
---
## Future Enhancements (Not in Phase 4)
Potential additions for future phases:
1. **Advanced Velocity Profiling**
- Velocity constraints per axis
- Velocity-dependent acceleration limits
- Look-ahead optimization
2. **More Geometric Primitives**
- Ellipses and elliptical arcs
- B-splines and Bézier curves
- Helical paths
- Lissajous curves
3. **Advanced Blending**
- Multi-segment blending (blend through multiple points)
- Velocity-dependent blend radius
- Orientation-specific blend control
4. **Full 6-DOF Transformations**
- Complete rotation matrix support
- Quaternion-based rotations
- Denavit-Hartenberg transformations
5. **Trajectory Optimization**
- Time-optimal trajectory planning
- Energy-optimal paths
- Obstacle avoidance
---
## Compatibility
### Python Version
- Requires Python 3.7+ (for type hints)
- Uses `Dict` and `List` from `typing` module
### Dependencies
- `numpy`: Used for array operations in helpers
- `math`: Used for trigonometric functions
- All dependencies already in RSIPI requirements
### RSI Configuration
- Requires Cartesian corrections (RKorr) configured
- No additional RSI XML changes needed
- Compatible with existing RSI 3.3 setup
---
## Documentation
### Code Documentation
- ✅ Comprehensive docstrings for all new methods
- ✅ Parameter descriptions with types and units
- ✅ Return value specifications
- ✅ Usage examples in docstrings
### Example Documentation
- ✅ 5 complete example programs
- ✅ Comprehensive README.md (584 lines)
- ✅ Inline comments in complex sections
- ✅ Real-world application scenarios
### User Documentation
- ✅ API reference in README
- ✅ Customization guide
- ✅ Troubleshooting section
- ✅ Performance optimization tips
---
## Lessons Learned
### Design Decisions
1. **Velocity Profiling Returns Tuples**
- Allows precise timing control per waypoint
- User can choose to ignore timing if not needed
- Flexible for different execution strategies
2. **Simple Coordinate Transforms**
- Chose translational + rotational offsets over full transformation matrices
- Sufficient for 90% of RSI applications
- Easier to understand and use
- Can be extended later if needed
3. **Static Methods in MotionAPI**
- Trajectory generation doesn't require API instance
- Can be used for offline planning
- Consistent with existing RSIPI architecture
4. **Cubic Hermite Spline for Blending**
- Zero velocity at endpoints ensures smooth transitions
- Simpler than quintic splines
- Sufficient for industrial applications
### Implementation Insights
1. **Edge Case Handling**
- Short trajectories need special handling in velocity profiling
- Blend radius must be validated against trajectory length
- Zero-radius cases need explicit checks
2. **Performance Trade-offs**
- More waypoints = smoother motion but longer generation time
- Typical industrial applications: 50-200 waypoints is optimal
- S-curve profiling is ~2x slower than trapezoidal but worth it
3. **Coordinate System Conventions**
- KUKA RSI uses right-handed coordinate systems
- Rotations follow KUKA's A, B, C convention
- Important to document frame assumptions clearly
---
## Statistics
### Code Metrics
- **New lines of code**: ~550 (motion_api.py)
- **Example code**: ~1,332 lines
- **Documentation**: ~584 lines (README.md)
- **Total additions**: ~2,466 lines
### Method Counts
- **New public methods**: 5
- **New helper functions**: 4
- **Total API methods**: 9 (including helpers)
### Example Counts
- **Example programs**: 5
- **Total examples**: 43 (across all examples)
- **Application scenarios**: 15+
---
## Next Phase
Phase 4 is now complete. The next phase in the roadmap is:
**Phase 6: Testing and Documentation**
- Comprehensive unit tests for all methods
- Integration tests with simulated robot
- API documentation generation
- User guide and tutorials
---
## Conclusion
Phase 4 successfully adds professional-grade motion planning capabilities to RSIPI. The implementation provides industrial-quality trajectory generation, velocity optimization, geometric primitives, path smoothing, and coordinate transformations suitable for production applications.
All features are well-documented, thoroughly tested with examples, and integrate seamlessly with existing RSIPI functionality. The phase is complete and ready for production use.
---
**Phase 4 Status**: ✅ **COMPLETE**
**Completion Date**: January 17, 2026

39
README.md
View File

@ -1,7 +1,7 @@
# RSIPI: Robot Sensor Interface for Python
[![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)
[![License: Apache 2.0](https://img.shields.io/badge/License-Apache_2.0-green.svg)](LICENSE)
RSIPI is a Python library for real-time control of KUKA industrial robots via the Robot Sensor Interface (RSI) protocol. The robot controller sends its state over UDP at a configurable cycle rate (4ms at 250Hz or 12ms at 83Hz), and RSIPI sends back position corrections, I/O commands, and Tech parameters. Communication uses XML packets over a dedicated Ethernet link, managed in a separate process so your control logic never blocks the real-time loop.
@ -577,6 +577,41 @@ The CLI provides the same capabilities as the Python API through text commands:
---
## How to Cite
If you use RSIPI in academic work, please cite it:
```bibtex
@software{morgan_rsipi,
author = {Morgan, Adam},
title = {{RSIPI}: Robot Sensor Interface for Python},
year = {2026},
url = {https://github.com/otherworld-dev/rsi-pi},
version = {0.1.1}
}
```
Or in plain text:
> Morgan, A. (2026). *RSIPI: Robot Sensor Interface for Python* (Version 0.1.1) [Computer software]. https://github.com/otherworld-dev/rsi-pi
A [CITATION.cff](CITATION.cff) file is included, so you can also use GitHub's
**Cite this repository** button for APA/BibTeX output.
---
## Support This Project
RSIPI is developed and maintained in spare time. If it saves you hours of
KUKA head-scratching, consider supporting development:
- [GitHub Sponsors](https://github.com/sponsors/otherworld-dev)
- [PayPal](https://www.paypal.com/donate/?hosted_button_id=MA56N6K8FSTQ2)
Bug reports, docs improvements, and pull requests are equally appreciated.
---
## License
MIT
[Apache License 2.0](LICENSE)

346
ROADMAP.md
View File

@ -1,346 +0,0 @@
# RSIPI Improvement Roadmap
**Goal:** Transform RSIPI into publication-quality research software for industrial robot control
**Status:** Phase 1 ✅ Complete | Phase 2 ✅ Complete | Phase 3 ✅ Complete | Phase 4 ✅ Complete | Phase 5 ✅ Complete | Phase 6 📋 Planned
---
## Overview
Six-phase improvement plan to make RSIPI world-class Python library for KUKA RSI control, suitable for publication in robotics research papers and industrial applications.
---
## ✅ Phase 1: Code Quality Foundation (COMPLETE)
**Objective:** Establish professional code quality baseline
**Completed Tasks:**
- ✅ Add comprehensive type hints to all core modules (500+ annotations)
- ✅ Create custom exception hierarchy (20+ specialized exceptions)
- ✅ Replace all print() statements with proper logging
- ✅ Add comprehensive docstrings with Args/Returns/Raises sections
- ✅ Improve error handling with exception chaining
**Files Modified:**
- `rsi_client.py` - State machine with typed exceptions
- `network_handler.py` - CSV logging and UDP communication
- `config_parser.py` - XML parsing with proper exception handling
- `safety_manager.py` - Safety validation with typed limits
- `exceptions.py` - NEW comprehensive exception hierarchy
**Commit:** `50e6df9` (January 16, 2026)
---
## ✅ Phase 2: Network Reliability (COMPLETE)
**Objective:** Ensure rock-solid network communication and diagnostics
**Completed Tasks:**
- ✅ Implement timing instrumentation (latency, jitter, cycle time tracking)
- ✅ Add watchdog timer for communication loss detection
- ✅ Implement network quality monitoring (packet loss, IPOC gaps, buffer health)
- ✅ Optimize CSV logging to prevent timing impact (batched updates every 100 cycles)
- ✅ Add auto-reconnection with graceful recovery
- ✅ Create 24-hour stability test infrastructure
**Deliverables:**
- Fully implemented `DiagnosticsAPI` namespace
- Real-time network health monitoring with TimingMetrics class
- Automatic recovery from network failures via AutoReconnectManager
- Comprehensive metrics tracking (cycle time, jitter, packet loss, IPOC gaps)
- 24-hour stability test script with JSON reporting
**Files Created/Modified:**
- `timing_metrics.py` - NEW TimingMetrics and NetworkQualityMonitor classes
- `auto_reconnect.py` - NEW AutoReconnectManager with retry strategies
- `network_handler.py` - Integrated timing metrics into real-time loop
- `rsi_client.py` - Added shared metrics dict and auto-reconnect support
- `diagnostics_api.py` - Fully implemented (was placeholder)
- `tests/stability_test.py` - NEW 24-hour stability test script
**API Methods:**
- `api.diagnostics.get_stats()` - Comprehensive network and performance statistics
- `api.diagnostics.get_timing()` - Timing-specific metrics
- `api.diagnostics.is_healthy()` - Overall system health check
- `api.diagnostics.get_network_quality()` - Network quality metrics
- `api.diagnostics.check_watchdog()` - Watchdog timeout status
- `api.diagnostics.format_stats()` - Human-readable statistics
**Commits:**
- `6e8ea2e` - Timing instrumentation and diagnostics (January 17, 2026)
- `bb65500` - Auto-reconnection and stability testing (January 17, 2026)
---
## ✅ Phase 3: KRL Coordination (COMPLETE)
**Objective:** Seamless Python-KRL coordination and communication
**Completed Tasks:**
- ✅ Implement high-level Digital I/O API (set_output, get_input, pulse)
- ✅ Add KRL state coordination helpers (wait_for_signal, signal_complete)
- ✅ Implement parameter passing via Tech variables (write_param, read_param)
- ✅ Create KRL code templates for all coordination scenarios (3 templates)
- ✅ Create Python coordination example workflows (3 examples)
**Deliverables:**
- Enhanced `IOAPI` with high-level I/O methods
- Enhanced `KRLAPI` with coordination helpers
- KRL template library (basic_handshake, parameter_passing, state_machine)
- Python coordination examples (3 production-ready scripts)
- Comprehensive documentation with KRL code examples
**Files Created/Modified:**
- `io_api.py` - Added set_output(), get_input(), pulse() methods
- `krl_api.py` - Added wait_for_signal(), signal_complete(), write_param(), read_param()
- `templates/krl/` - 3 KRL templates + README with coordination patterns
- `examples/coordination/` - 3 Python examples + README with usage guide
**API Methods:**
- `api.io.set_output(channel, value)` - Set digital output by channel
- `api.io.get_input(channel)` - Read digital input by channel
- `api.io.pulse(channel, duration)` - Generate timed output pulse
- `api.krl.wait_for_signal(channel, timeout)` - Wait for KRL I/O signal
- `api.krl.signal_complete(channel)` - Signal KRL completion
- `api.krl.write_param(slot, value)` - Write to Tech.C (Python → KRL)
- `api.krl.read_param(slot)` - Read from Tech.T (KRL → Python)
**Commit:** `6e0b87b` (January 17, 2026)
---
## ✅ Phase 4: Advanced Motion Control (COMPLETE)
**Objective:** Professional-grade trajectory planning and execution
**Completed Tasks:**
- ✅ Implement velocity profiling (trapezoidal, S-curve)
- ✅ Add coordinate frame transformation helpers
- ✅ Implement motion primitives (arc, circle, spiral)
- ✅ Add path blending for smooth transitions
- ✅ Create comprehensive motion planning examples (5 examples)
- ✅ Document all features with application use cases
**Deliverables:**
- Enhanced `MotionAPI` with 5 new advanced planning methods
- Velocity profiling algorithms (trapezoidal and S-curve)
- Geometric motion primitives (arc, circle, spiral)
- Path blending with cubic Hermite spline interpolation
- Coordinate transformations between BASE/WORLD/TOOL/WORK frames
- 5 production-ready motion planning examples
- Comprehensive documentation (584-line README.md)
**Files Created/Modified:**
- `motion_api.py` - Added 5 static methods + 4 helper functions (~550 lines)
- `examples/advanced_motion/01_velocity_profiles.py` - NEW (234 lines)
- `examples/advanced_motion/02_geometric_primitives.py` - NEW (225 lines)
- `examples/advanced_motion/03_path_blending.py` - NEW (253 lines)
- `examples/advanced_motion/04_coordinate_transforms.py` - NEW (284 lines)
- `examples/advanced_motion/05_combined_motion.py` - NEW (336 lines)
- `examples/advanced_motion/README.md` - NEW comprehensive guide (584 lines)
- `PHASE_4_SUMMARY.md` - NEW detailed implementation documentation
**API Methods:**
- `api.motion.generate_velocity_profile(trajectory, max_velocity, max_acceleration, profile)`
- `api.motion.generate_arc(center, radius, start_angle, end_angle, steps, plane)`
- `api.motion.generate_circle(center, radius, steps, plane)`
- `api.motion.generate_spiral(center, start_radius, end_radius, pitch, revolutions, steps, plane, axis)`
- `api.motion.blend_trajectories(traj1, traj2, blend_radius, blend_steps)`
- `api.motion.transform_coordinates(pose, from_frame, to_frame, frame_offset)`
**Commit:** `cc19e10` (January 17, 2026)
---
## ✅ Phase 5: API Restructuring (COMPLETE)
**Objective:** Clean, namespaced API architecture
**Completed Tasks:**
- ✅ Create SafetyAPI namespace class
- ✅ Create IOAPI namespace class
- ✅ Create MonitoringAPI namespace class
- ✅ Create LoggingAPI namespace class
- ✅ Create KRLAPI namespace class
- ✅ Create ToolsAPI namespace class
- ✅ Create VizAPI namespace class
- ✅ Create MotionAPI namespace class
- ✅ Create DiagnosticsAPI placeholder class
- ✅ Restructure RSIAPI as orchestrator with namespace properties
**New Namespace Structure:**
```python
api = RSIAPI('RSI_EthernetConfig.xml')
api.motion # Motion control
api.io # Digital I/O
api.krl # KRL manipulation
api.safety # Safety management
api.monitoring # Live data access
api.logging # CSV logging
api.diagnostics # Network diagnostics
api.viz # Visualization
api.tools # Utilities
```
**Breaking Changes:**
- No backward compatibility (clean slate)
- Old API completely replaced with namespaced structure
**Files Created:**
- `motion_api.py`, `io_api.py`, `krl_api.py`, `safety_api.py`
- `monitoring_api.py`, `logging_api.py`, `diagnostics_api.py`
- `viz_api.py`, `tools_api.py`
**Commit:** `50e6df9` (January 16, 2026)
---
## 📋 Phase 6: Validation & Benchmarking (PLANNED)
**Objective:** Prove production-readiness and publish results
**Planned Tasks:**
1. Create performance benchmark suite (vs ROS, vs KUKA SDK)
2. Run long-duration stability tests with real robot
3. Document example applications and use cases
**Expected Deliverables:**
- Benchmark comparison report (RSIPI vs ROS vs KUKA SDK)
- 24-hour+ stability test results
- Latency/jitter performance analysis
- Example applications repository
- Use case documentation
- Publication-ready performance data
**Benchmark Metrics:**
- Communication latency (round-trip time)
- Jitter and timing variance
- Maximum sustainable update rate
- CPU/memory overhead comparison
- Reliability (packet loss, connection uptime)
---
## Project Structure After All Phases
```
rsi-pi/
├── src/RSIPI/
│ ├── rsi_api.py # Main orchestrator
│ ├── rsi_client.py # Core RSI client
│ ├── motion_api.py # Motion control namespace
│ ├── io_api.py # Digital I/O namespace
│ ├── krl_api.py # KRL manipulation namespace
│ ├── safety_api.py # Safety management namespace
│ ├── monitoring_api.py # Monitoring namespace
│ ├── logging_api.py # CSV logging namespace
│ ├── diagnostics_api.py # Network diagnostics namespace
│ ├── viz_api.py # Visualization namespace
│ ├── tools_api.py # Utilities namespace
│ ├── network_handler.py # UDP communication
│ ├── config_parser.py # XML config parsing
│ ├── safety_manager.py # Safety validation
│ ├── exceptions.py # Exception hierarchy
│ ├── xml_handler.py # XML generation
│ ├── trajectory_planner.py # Trajectory generation
│ ├── static_plotter.py # Static plots
│ ├── live_plotter.py # Live plots
│ ├── krl_to_csv_parser.py # KRL parsing
│ ├── inject_rsi_to_krl.py # KRL injection
│ └── kuka_visualiser.py # Visualization
├── tests/ # Test suite
├── examples/ # Example applications
├── benchmarks/ # Performance benchmarks
├── docs/ # Documentation
├── README.md
└── RSIPI_ROADMAP.md # This file
```
---
## Success Criteria
**Phase 1 & 5 (Complete):**
- ✅ 500+ type annotations across codebase
- ✅ 20+ custom exceptions with proper hierarchy
- ✅ Zero print() statements (all logging)
- ✅ Comprehensive docstrings on all public methods
- ✅ 9 namespaced API classes with clean separation
- ✅ Professional API design pattern
**Phase 2 (Complete):**
- ✅ Real-time network quality monitoring
- ✅ Automatic recovery from network failures
- ✅ Comprehensive diagnostics dashboard
- ✅ TimingMetrics tracking (cycle time, jitter, packet loss)
- ✅ AutoReconnectManager with configurable retry strategies
- ✅ 24-hour stability test infrastructure
- ⏳ Run actual 24-hour stability test (pending hardware)
**Phase 3 (Complete):**
- ✅ High-level I/O API with pulse generation (set_output, get_input, pulse)
- ✅ Python-KRL coordination patterns documented (templates/krl/README.md)
- ✅ Tech variable parameter passing working (write_param, read_param)
- ✅ KRL template library created (3 templates with full workflows)
- ✅ Example coordination workflows (3 Python examples with documentation)
**Phase 4 (Complete):**
- ✅ Trapezoidal and S-curve velocity profiles implemented
- ✅ Arc, circle, spiral motion primitives created
- ✅ Path blending with cubic interpolation and configurable blend radius
- ✅ Coordinate frame transformations (BASE/WORLD/TOOL/WORK)
- ✅ Smooth continuous motion demonstrated in examples
- ✅ 5 comprehensive production-ready examples
- ✅ 584-line documentation guide created
**Phase 6 (Planned):**
- Performance benchmarks vs ROS/KUKA SDK
- Publication-ready data and graphs
- Long-duration stability proven
- Multiple example applications
- Use cases documented
---
## Timeline
- **Phase 1:** ✅ Complete (January 16, 2026)
- **Phase 2:** ✅ Complete (January 17, 2026)
- **Phase 3:** ✅ Complete (January 17, 2026)
- **Phase 4:** ✅ Complete (January 17, 2026)
- **Phase 5:** ✅ Complete (January 16, 2026)
- **Phase 6:** 📋 Next priority - Final validation
**Approach:** "Get it right the first time" - complete each phase fully before moving to the next.
---
## Research Publication Goal
**Target:** High-quality research paper demonstrating RSIPI as lightweight, high-performance alternative to ROS for KUKA robot control in drilling/manufacturing applications.
**Key Points:**
- Python-based, easy to integrate
- ~250Hz update rate, <5ms latency
- Industrial-grade reliability
- Comprehensive safety features
- Minimal dependencies
- Professional API design
- Proven stability (24-hour tests)
- Benchmarked against ROS
---
## Notes
- No backward compatibility - clean slate design
- Focus on quality over speed
- All features properly documented
- Type-safe with comprehensive testing
- Suitable for industrial research applications
- Designed for drilling PhD research (but general-purpose)
**Last Updated:** January 17, 2026

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# KUKA Controller Setup Guide
Getting RSIPI talking to a real robot: installing the config files on a KRC4
controller, configuring the network, and troubleshooting the common failure
modes.
Primary source: the official **KUKA.RobotSensorInterface 3.3 manual**
(KST RSI 3.3 V5, issued 2016-10-17, for KSS 8.3/8.4), available from KUKA
via [my.kuka.com](https://my.kuka.com) or your KUKA support contact (it is
KUKA-copyrighted, so it is not redistributed with this repo). Section/page
references below (e.g. "manual §8.1.1, p. 56") point into that document. Claims not covered by the
manual are marked *(practical experience)* and sourced at the bottom.
## Prerequisites
- **KRC4 controller** with **KSS 8.3 or 8.4** and the
**KUKA.RobotSensorInterface 3.x** option package installed
(manual §4.1, p. 25). Check **Help > Info > Options** on the pendant.
RSI provides `RSI_CREATE`, `RSI_ON`, `RSI_MOVECORR`, `RSI_OFF`,
`RSI_DELETE` (manual §7.1, p. 39).
- RSI must **not** be installed together with KUKA.ConveyorTech or
KUKA.ServoGun TC (manual §4.1, p. 25).
- For corrections in `#IPO` sensor mode, **function generator 1 must be
free** (manual §4.1, p. 25; configurable via `RSITECHIDX` in
`KRC:\R1\TP\RSI\RSI.DAT`, manual §5.2, p. 30).
- PC side: Python 3.10+ with RSIPI installed (`pip install -e .`), on a
network interface reachable from the controller. KUKA specifies a
"real-time-capable operating system and real-time-capable network card
with 100 Mbit in full duplex mode" (manual §4.1, p. 25) — a normal
Windows/Linux PC works for testing but is not real-time capable, so
expect occasional late packets (see [Timing](#timing-requirements)).
## 1. Install the files
The files in `rsi_config/` go to **two different places**. This split is
specified in manual §8.1.1, p. 56:
> 2. Copy KRL programs into the directory `C:\KRC\ROBOTER\KRC\R1\Program`
> of the robot controller.
> 3. Copy the sample configurations and the XML file for the Ethernet
> connection to the directory
> `C:\KRC\ROBOTER\Config\User\Common\SensorInterface` of the robot
> controller.
| File | Destination on controller |
|---|---|
| `RSIPI_Full.rsi` | `C:\KRC\ROBOTER\Config\User\Common\SensorInterface\` |
| `RSIPI_Full.rsi.diagram` | `C:\KRC\ROBOTER\Config\User\Common\SensorInterface\` |
| `RSIPI_Full.rsi.xml` | `C:\KRC\ROBOTER\Config\User\Common\SensorInterface\` |
| `RSI_EthernetConfig_Full.xml` | `C:\KRC\ROBOTER\Config\User\Common\SensorInterface\` |
| `RSIPI_Minimal.src` | `C:\KRC\ROBOTER\KRC\R1\Program\` (= `KRC:\R1\Program` in the Navigator) |
| `RSIPI_Test.src` | `C:\KRC\ROBOTER\KRC\R1\Program\` (= `KRC:\R1\Program` in the Navigator) |
Watch the paths carefully — they are confusingly similar:
- KRL programs go under `...\ROBOTER\KRC\R1\Program` (**with** `\KRC\`).
- SensorInterface files go under `...\ROBOTER\Config\User\Common\...`
(**without** a second `\KRC\`). Putting them in
`C:\KRC\ROBOTER\KRC\Config\User\Common\SensorInterface` is a common
mistake; `RSI_CREATE` will not find them there.
- A `.src` file placed in the SensorInterface folder never appears as a
program, and a program that isn't loaded through `KRC:\R1\Program` throws
"variable not defined" on every RSI keyword.
Notes:
- The RSI, DIAGRAM and XML files "form a unit and must be transferred to
the robot controller together" (manual §8.1, p. 55).
- **Do not rename the files.** `RSIPI_Full.rsi` references
`RSI_EthernetConfig_Full.xml` by name in its ETHERNET object, and the
`.src` programs load `"RSIPI_Full.rsi"` by name in `RSI_CREATE`.
- Copy `.src` files as the **Expert** user group (log on via
Configuration > User group).
## 2. Configure the network
RSI needs "its own Ethernet sensor network which is independent of other
KLI subnetworks", physically connected via the KLI ports X66 or X67.1-3 on
the controller cabinet (manual §5.1, p. 29).
### Controller side
Two documented ways to set the robot's RSI IP address (manual §5.1.1 and
§5.1.2, pp. 29–30):
**A. KLI network configuration on the pendant** (requires KSS 8.3.15+,
Expert group, T1/T2, no program selected):
1. Main menu > **Start-up > Network configuration** > **Advanced...**
2. **Add interface**; name it (e.g. "Ethernet sensor network").
3. Set **Address type: Mixed IP address** — this auto-creates the
real-time UDP receiving tasks RSI needs.
4. Enter the robot's IP and subnet mask, **Save**, and **reboot the
controller**.
**B. RSI-Network tool in Windows** (Expert group): minimize the HMI
(Start-up > Service > Minimize HMI), run **All Programs > RSI-Network**,
select the entry **New** under *RSI Ethernet* in the tree, press **Edit**,
enter the robot controller's IP, confirm, then **cold restart** the
controller.
IP address rules (manual §5.1.1, p. 29):
- PC and controller must be "located in the same network segment", i.e.
only the last of the 4 octets may differ.
- "The IP address range **192.168.0.x is blocked**" and the address "must
not be in the address range of another KLI subnet". The manual's example
uses robot `192.168.1.2` / mask `255.255.255.0` with the sensor (PC) at
`192.168.1.1`. This repo's default config uses `10.10.10.x`, which
safely avoids all KUKA-internal ranges *(practical experience — see
Sources)*.
### "Address already in use" when adding the interface
This error is not documented in the manual *(practical experience)*: it
appears when the address you enter collides with an interface entry that
already exists — a leftover RSI Ethernet entry, or another KLI subnet
containing the same address. Fix: in the interface tree, **edit or delete
the existing entry instead of adding a second one** (note the documented
RSI-Network procedure edits the existing "New" entry rather than creating
another), and make sure the subnet doesn't overlap any other configured
interface. Reboot (cold restart) afterwards — network changes only take
effect after a reboot (manual §5.1.1 step 8 / §5.1.2 step 5, p. 30).
### PC side
Give the PC a **static IP** on the RSI link and put that address in
`RSI_EthernetConfig_Full.xml` (both the copy on the controller and the copy
the Python side loads — they must match):
```xml
<CONFIG>
<IP_NUMBER>10.10.10.10</IP_NUMBER> <!-- your PC's IP -->
<PORT>64000</PORT>
<SENTYPE>ImFree</SENTYPE>
<ONLYSEND>FALSE</ONLYSEND>
</CONFIG>
```
Pick a free UDP port "not assigned a standard service" (manual §8.1.2.1,
p. 58). Allow that UDP port through the PC firewall, or disable the
firewall on the dedicated RSI interface *(practical experience)* — a
blocked firewall shows up as "Python receives nothing" while a packet
capture still sees traffic arriving.
### Timing requirements
The robot controller initiates the exchange and sends a packet every
sensor cycle; "a data packet received by the sensor system must be
answered within the sensor cycle rate. Packets that arrive too late are
rejected. When the maximum number of data packets for which a response has
been sent too late has been exceeded, the robot stops." (manual §2.3.2,
p. 15). The sensor cycle is **4 ms** in `#IPO_FAST` (default) or **12 ms**
in `#IPO` mode (manual §7.1.4, p. 41). The allowed number of late packets
is the `Timeout` parameter of the ETHERNET object — set to 100 in
`RSIPI_Full.rsi`.
## 3. First run: minimal test
`RSIPI_Minimal.src` mirrors KUKA's official `RSI_Ethernet.src` example
(manual §8.1.3, p. 59: `RSI_CREATE` → `RSI_ON(#RELATIVE)` →
`RSI_MOVECORR()` → `RSI_OFF`) and uses no `$TECH` variables, no I/O and no
`$SEN_PREA` — so it isolates "does RSI work at all" from everything else.
1. On the pendant (T1 mode, low override): select `RSIPI_Minimal` and start
it. It does a BCO run to the current position, activates RSI, and reports
*"RSI active - start the Python sender now"*. The robot holds position,
waiting for corrections.
2. On the PC, from the repo root:
```python
from RSIPI import RSIAPI
api = RSIAPI("RSI_EthernetConfig_Full.xml")
api.start()
if not api.wait_for_connection(timeout=30.0):
raise SystemExit("No packets from robot - see troubleshooting table")
print("Connected:", api.motion.get_current_pose())
api.motion.update_cartesian(X=5.0) # small 5mm correction
input("Press Enter to stop...")
api.stop()
```
3. Stop by cancelling the program on the pendant. Stopping the Python side
instead also works: after `Timeout` late packets the robot stops and
reports an RSI communication error — expected and safe (manual §2.3.2,
p. 15). (A clean stop signal would require a STOP object in the signal
flow, manual §7.1.6, p. 42 — `RSIPI_Full.rsi` doesn't include one.)
Keep first corrections small. The signal flow limits Cartesian corrections
to ±500 mm (`POSCORR1` in `RSIPI_Full.rsi`), which is generous — tighten it
in RSI Visual and/or set software limits on the Python side via
`api.safety.set_limit()` before doing anything real.
Independent cross-check: KUKA ships a Windows test server (`TestServer.exe`)
with the RSI option package for exactly this purpose (manual §8.1.2, p. 56)
— find it on the controller under
`D:\KUKA_OPT\RSI\DOC\Examples\Ethernet\Server` (manual §8.1, p. 55). If the
robot exchanges packets with TestServer but not with RSIPI, the problem is
on the Python/firewall side, not the robot.
## 4. Full test
`RSIPI_Test.src` + `rsi_config/rsipi_test.py` exercise the whole feature
set: corrections, `$SEN_PREA` (via MAP2SEN_PREA objects, manual §11.2.10,
p. 81), digital I/O, and a handshake over the `Tech.C` / `Tech.T` channels.
Those channels are "technology parameters in the main run / advance run
(function generators 1 to 6)" (manual §7.4.5–7.4.6, pp. 52–53): on the
wire, `DEF_Tech.C1` carries the ten parameters of function generator 1 as
attributes `C11…C110`.
On the KRL side the test program reads/writes these as `$TECH.C[11]` etc.
On at least one user's KSS 8.3.38 installation these `$TECH` references
fail to load with "variable not defined"
([issue #1](https://github.com/otherworld-dev/rsi-pi/issues/1)) — the
variables appear tied to a technology-package installation, and the exact
availability conditions haven't been pinned down yet. **If only the
`$TECH.…` lines error, run `RSIPI_Minimal.src` instead** — everything
except the Tech handshake works without them.
## 5. Troubleshooting
| Symptom | Likely cause | Fix |
|---|---|---|
| "Variable not defined" on **every** line / `RSI_CREATE`, `RSI_ON`, `RSIOK` unknown | `.src` file not in `KRC:\R1\Program`, or RSI option not installed | Move the `.src` (see §1); check RSI appears under Help > Info > Options |
| "Variable not defined" only on `$TECH.…` lines | `$TECH` technology parameters not available on this installation | Use `RSIPI_Minimal.src` (see §4) |
| "Address already in use" when creating the RSI Ethernet entry | An interface entry with that address/subnet already exists | Edit or delete the existing entry instead of adding a new one; reboot (see §2) |
| `RSI_CREATE` returns `RSIFILENOTFOUND` / `RSIINVFILE` | Config files missing from `Config\User\Common\SensorInterface` (check for the extra-`\KRC\` path mistake), renamed, or `.rsi`/`.rsi.xml`/`.diagram` set incomplete | Re-copy all four config files together, keep original names (manual §7.1.2, p. 40 for return codes) |
| `RSI_ON` fails / RSI communication error immediately | IP in `RSI_EthernetConfig_Full.xml` doesn't match the PC, or subnet mismatch (only last octet may differ), or PC in `192.168.0.x` | Fix `<IP_NUMBER>`; follow the IP rules in §2 |
| Robot program runs but Python sees no packets | PC firewall blocking the UDP port, or RSIPI bound to the wrong interface | Allow the port / disable firewall on the RSI interface; verify with KUKA's `TestServer.exe` (see §3) |
| Robot stops mid-motion with RSI error after running fine | Response packets late: Python loop blocked, or non-dedicated network | Keep the correction loop free of blocking work; use a dedicated interface; watch the `Delay` variable (count of late packets, manual §7.4.5, p. 52) |
| Corrections apply but motion is jerky | Late/rejected packets | Same as above — dedicated network, faster loop |
Still stuck? Open an issue with your KSS version, RSI version (Help > Info >
Options), and the exact pendant error message.
## Sources
- **KUKA.RobotSensorInterface 3.3** manual, KST RSI 3.3 V5, KUKA Roboter
GmbH, 2016-10-17 — from KUKA ([my.kuka.com](https://my.kuka.com)).
All "manual §…" references above.
- [Michael Sobrepera, "KUKA Setup Guide"](https://michaelsobrepera.com/guides/kuka.html)
— practical KRC4 + RSI walkthrough (network interface creation, firewall,
file copying).
- Robot-Forum: [KRC4 RSI Ethernet](https://www.robot-forum.com/robotforum/thread/12240-krc4-rsi-ethernet/)
and [IP addresses in network configuration of KRC4](https://www.robot-forum.com/robotforum/thread/16990-ip-addresses-in-network-configuration-of-krc4/)
— reserved KRC4 subnets (`192.168.0.x` shared-memory driver) and RSI
network setup experience.

1
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@ -561,7 +561,6 @@ for i in range(len(layers) - 1):
## References
- [RSIPI API Documentation](../../README.md)
- [Phase 4 Implementation Summary](../../PHASE_4_SUMMARY.md) (when available)
- [Basic Motion Examples](../basic_motion/)
- [Coordination Examples](../coordination/)
- [KUKA RSI 3.3 Manual](https://www.kuka.com)

4
pyproject.toml
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@ -10,7 +10,7 @@ readme = "README.md"
requires-python = ">=3.8"
license = { file = "LICENSE" }
authors = [
{ name="Adam Morgan", email="yadam.j.morgan@swansea.ac.uk" }
{ name="Adam Morgan", email="contact@otherworld.dev" }
]
dependencies = [
"pandas>=2.0",
@ -21,7 +21,7 @@ dependencies = [
]
classifiers = [
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"License :: OSI Approved :: Apache Software License",
"Operating System :: OS Independent",
]

74
rsi_config/RSIPI_Minimal.src Normal file
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@ -0,0 +1,74 @@
&ACCESS RVP
&REL 1
DEF RSIPI_Minimal()
; =========================================================================
; RSIPI Minimal Test Program
; =========================================================================
; Bare-bones RSI check with NO dependency on the Technology package:
; - no $TECH.C[] / $TECH.T[] variables
; - no digital I/O, no $SEN_PREA
;
; It only verifies that:
; 1. The RSI context (RSIPI_Full.rsi) loads -> RSI_CREATE
; 2. RSI activates and the UDP link comes up -> RSI_ON
; 3. Corrections streamed from Python are applied -> RSI_MOVECORR
;
; Use this first if RSIPI_Test.src reports "variable not defined" on
; $TECH lines (Technology package missing/not licensed) or to prove
; the network link before running the full test.
;
; Python side: any correction sender works, e.g.
; examples/example_02_send_cartesian.py
; started AFTER RSI_MOVECORR is reached (robot waits, holding position).
;
; To stop: cancel the program on the pendant, or stop the Python side
; and let the ETHERNET object time out (motion stops, RSI reports a
; communication error - this is expected and safe).
;
; See docs/controller-setup.md for installation and troubleshooting.
; =========================================================================
DECL INT ret, CONTID
INI
; BCO run to the current position
PTP $POS_ACT
; -- Load RSI signal flow configuration -----------------------------------
; RSIPI_Full.rsi must be in Config\User\Common\SensorInterface
ret = RSI_CREATE("RSIPI_Full.rsi", CONTID, TRUE)
IF (ret <> RSIOK) THEN
MsgNotify("RSI_CREATE failed - check SensorInterface files", "RSIPI_Minimal")
HALT
ENDIF
; -- Activate RSI ----------------------------------------------------------
; RELATIVE corrections in the default #IPO_FAST sensor mode (4ms cycle),
; exactly like KUKA's own RSI_Ethernet example (KST RSI 3.3 manual, 8.1.3).
; Do not pass #IPO here: in IPO mode corrections only apply to LIN/CIRC
; path motions and function generator 1 must be free (manual 4.1, 7.1.4).
ret = RSI_ON(#RELATIVE)
IF (ret <> RSIOK) THEN
MsgNotify("RSI_ON failed - check network config", "RSIPI_Minimal")
HALT
ENDIF
MsgNotify("RSI active - start the Python sender now", "RSIPI_Minimal")
; -- Sensor-guided motion --------------------------------------------------
; The robot holds position and applies RKorr corrections streamed from
; Python. Blocks until the program is cancelled or RSI stops.
RSI_MOVECORR()
; -- Clean up ----------------------------------------------------------------
ret = RSI_OFF()
IF (ret <> RSIOK) THEN
MsgNotify("RSI_OFF warning", "RSIPI_Minimal")
ENDIF
ret = RSI_DELETE(CONTID)
MsgNotify("RSIPI_Minimal complete", "RSIPI_Minimal")
END

8
setup.py
View File

@ -6,9 +6,9 @@ setup(
description="Robot Sensor Interface Python Integration (RSIPI) for KUKA RSI control",
long_description=open("README.md", encoding="utf-8").read(),
long_description_content_type="text/markdown",
author="YAdam Morgan",
author_email="adam.j.morgan@swansea.ac.uk",
license="MIT",
author="Adam Morgan",
author_email="contact@otherworld.dev",
license="Apache-2.0",
python_requires=">=3.8",
packages=find_packages(where="src"),
package_dir={"": "src"},
@ -21,7 +21,7 @@ setup(
],
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"License :: OSI Approved :: Apache Software License",
"Operating System :: OS Independent",
],
include_package_data=True,

437
src/RSIPI.egg-info/PKG-INFO
View File

@ -1,437 +0,0 @@
Metadata-Version: 2.4
Name: RSIPI
Version: 0.1.1
Summary: Robot Sensor Interface Python Integration (RSIPI) for KUKA RSI control
Author: YAdam Morgan
Author-email: Adam Morgan <yadam.j.morgan@swansea.ac.uk>
License: GNU AFFERO GENERAL PUBLIC LICENSE
Version 3, 19 November 2007
Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>
Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed.
Preamble
The GNU Affero General Public License is a free, copyleft license for software and other kinds of works, specifically designed to ensure cooperation with the community in the case of network server software.
The licenses for most software and other practical works are designed to take away your freedom to share and change the works. By contrast, our General Public Licenses are intended to guarantee your freedom to share and change all versions of a program--to make sure it remains free software for all its users.
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TERMS AND CONDITIONS
0. Definitions.
"This License" refers to version 3 of the GNU Affero General Public License.
"Copyright" also means copyright-like laws that apply to other kinds of works, such as semiconductor masks.
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If the disclaimer of warranty and limitation of liability provided above cannot be given local legal effect according to their terms, reviewing courts shall apply local law that most closely approximates an absolute waiver of all civil liability in connection with the Program, unless a warranty or assumption of liability accompanies a copy of the Program in return for a fee.
END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest possible use to the public, the best way to achieve this is to make it free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest to attach them to the start of each source file to most effectively state the exclusion of warranty; and each file should have at least the "copyright" line and a pointer to where the full notice is found.
RSI-PI
Copyright (C) 2025 adam
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Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=2.0
Requires-Dist: numpy>=1.22
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Provides-Extra: dev
Requires-Dist: pytest>=7.0; extra == "dev"
Dynamic: author
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Dynamic: requires-python
# RSIPI: Robot Sensor Interface - Python Integration
RSIPI is a high-performance, Python-based communication and control system designed for real-time interfacing with KUKA robots using the Robot Sensor Interface (RSI) protocol. It provides both a robust **API** for developers and a powerful **Command Line Interface (CLI)** for researchers and engineers who need to monitor, control, and analyse robotic movements in real time.
---
🛡️ Safety Notice
RSIPI is a powerful tool that directly interfaces with industrial robotic systems. Improper use can lead to dangerous movements, property damage, or personal injury.
⚠️ Safety Guidelines
- **Test in Simulation First:** Always verify your RSI communication and trajectories using simulation tools before deploying to a live robot.
- **Enable Emergency Stops:** Ensure all safety hardware (E-Stop, fencing, light curtains) is active and functioning correctly.
- **Supervised Operation Only:** Run RSIPI only in supervised environments with trained personnel present.
- **Limit Movement Ranges:** Use KUKA Workspaces or software limits to constrain movement, especially when testing new code.
- **Use Logging for Debugging:** Avoid debugging while RSI is active; instead, enable CSV logging and review logs post-run.
- **Secure Network Configuration:** Ensure your RSI network is on a closed, isolated interface to avoid external interference or spoofing.
- **Never Rely on RSIPI for Safety:** RSIPI is not a safety-rated system. Do not use it in applications where failure could result in harm.
---
## 📄 Description
RSIPI allows users to:
- Communicate with KUKA robots using the RSI XML-based protocol.
- Dynamically update control variables (TCP position, joint angles, I/O, external axes, etc.).
- Log and visualise robot movements with live graphs and static plots.
- Analyse motion data and compare planned vs actual trajectories.
- Parse and inject RSI into KRL programs.
- Simulate robot behaviour using a realistic Echo Server.
- Enforce safety limits and manage emergency stops.
### Target Audience
- **Researchers** working on advanced robotic applications, control algorithms, and feedback systems.
- **Engineers** developing robotic workflows or automated processes.
- **Educators** using real robots in coursework or lab environments.
- **Students** learning about robot control systems and data-driven motion planning.
---
## 📊 Features
- Real-time network communication with KUKA RSI over UDP.
- Structured logging to CSV with British date formatting.
- Background execution and live variable updates.
- Fully-featured Python API for scripting or external integration.
- CLI for interactive control, trajectory planning, and live monitoring.
- Real-time and post-analysis graphing (live TCP, joints, force, acceleration).
- Safety management: emergency stop, limit enforcement, safety override.
- KUKA KRL `.src/.dat` parsing and RSI injection tools.
- Echo Server and GUI for offline simulation and testing.
- Deviation and force spike alerts during live operation.
---
## 📊 API Overview (`rsi_api.py`)
### Initialization
```python
from src.RSIPI import rsi_api
api = rsi_api.RSIAPI(config_file='examples/RSI_EthernetConfig.xml')
```
### Selected Methods
| Method | CLI | API | Description |
|--------|-----|-----|-------------|
| `start_rsi()` | ✅ | ✅ | Starts RSI communication (non-blocking). |
| `stop_rsi()` | ✅ | ✅ | Stops RSI communication. |
| `update_variable(path, value)` | ✅ | ✅ | Dynamically updates a send variable (e.g. `RKorr.X`). |
| `get_variable(path)` | ✅ | ✅ | Retrieves the latest value of any variable. |
| `plan_linear_cartesian(start, end, steps)` | ✅ | ✅ | Create Cartesian paths. |
| `plan_linear_joint(start, end, steps)` | ✅ | ✅ | Create Joint-space paths. |
| `execute_trajectory(traj, rate)` | ✅ | ✅ | Execute planned trajectory live. |
| `enable_alerts(True/False)` | ✅ | ✅ | Enable or disable deviation/force alerts. |
| `start_live_plot(mode)` | ✅ | ✅ | Live graph position, velocity, force, etc. |
| `generate_plot(csv, type)` | ✅ | ✅ | Static graphing from CSV files. |
| `export_movement_data(filename)` | ✅ | ✅ | Export recorded motion as CSV. |
| `parse_krl_to_csv(src, dat, output)` | ✅ | ✅ | Extract TCP points from KRL programs. |
| `inject_rsi(input, output, config)` | ✅ | ✅ | Add RSI startup code to a KRL file. |
_(Full API details available in `rsi_api.py`.)_
---
## 🔧 CLI Overview (`rsi_cli.py`)
Start the CLI:
```bash
python main.py --cli
```
### Selected Commands
| Command | Description |
|---------|-------------|
| `start` / `stop` | Start or stop RSI client. |
| `set <var> <value>` | Update send variable. |
| `get <var>` | Get latest receive variable. |
| `move_cartesian`, `move_joint` | Move robot using planned trajectories. |
| `queue_cartesian`, `queue_joint` | Queue trajectory steps. |
| `execute_queue` | Run queued trajectories. |
| `alerts on/off` | Enable or disable alerts. |
| `graph show/compare` | Plot or compare test runs. |
| `log start/stop/status` | Manage CSV logging. |
| `plot <type> <csv>` | Static plotting (position, velocity, deviation, etc.). |
| `safety-stop`, `safety-reset`, `safety-status` | Emergency stop and limit management. |
| `krlparse <src> <dat> <out>` | Parse KRL to CSV. |
| `inject_rsi <src> [out] [config]` | Inject RSI code into KRL file. |
---
## 📃 Example Usage
### Update TCP position live
```python
api.start_rsi()
api.update_variable('RKorr.X', 100.0)
api.update_variable('RKorr.Y', 50.0)
```
### Plan and execute a Cartesian move
```python
start_pose = {'X': 0, 'Y': 0, 'Z': 500}
end_pose = {'X': 200, 'Y': 0, 'Z': 500}
traj = api.plan_linear_cartesian(start_pose, end_pose, steps=100)
api.execute_trajectory(traj, rate=0.012)
```
### CLI session sample
```bash
> start
> set RKorr.X 150
> move_cartesian X=0,Y=0,Z=500 X=200,Y=0,Z=500 steps=100 rate=0.012
> graph show my_log.csv
> log start
> stop
```
---
## 📅 Output and Logs
- CSV logs saved to `logs/` folder.
- Each log includes British timestamp, sent/received variables.
- Static plots exportable as PNG/PDF.
- Live plots include alert messages and deviation tracking.
---
## 🚀 Getting Started
1. Connect robot and PC via Ethernet.
2. Deploy KUKA RSI program with matching config.
3. Install Python dependencies:
```bash
pip install -r requirements.txt
```
4. Run `main.py` or import `RSIAPI` in your Python scripts.
---
## 🔖 Citation
If you use RSIPI in your research, please cite:
```bibtex
@software{rsipi2025,
author = {RSIPI Development Team},
title = {RSIPI: Robot Sensor Interface - Python Integration},
year = {2025},
url = {https://github.com/your-org/rsipi},
note = {Accessed: [insert date]}
}
```
---
## ⚖️ License
RSIPI is licensed under the MIT License.
---
## 🚧 Disclaimer
RSIPI is intended for research and experimental purposes only. Always ensure safe operation with appropriate safety measures in place.

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LICENSE
MANIFEST.in
README.md
pyproject.toml
setup.py
src/RSIPI/__init__.py
src/RSIPI/auto_reconnect.py
src/RSIPI/config_parser.py
src/RSIPI/diagnostics_api.py
src/RSIPI/echo_server_gui.py
src/RSIPI/exceptions.py
src/RSIPI/inject_rsi_to_krl.py
src/RSIPI/io_api.py
src/RSIPI/krl_api.py
src/RSIPI/krl_to_csv_parser.py
src/RSIPI/kuka_visualiser.py
src/RSIPI/live_plotter.py
src/RSIPI/logging_api.py
src/RSIPI/monitoring_api.py
src/RSIPI/motion_api.py
src/RSIPI/network_handler.py
src/RSIPI/rsi_api.py
src/RSIPI/rsi_cli.py
src/RSIPI/rsi_client.py
src/RSIPI/rsi_config.py
src/RSIPI/rsi_echo_server.py
src/RSIPI/rsi_graphing.py
src/RSIPI/rsi_limit_parser.py
src/RSIPI/safety_api.py
src/RSIPI/safety_manager.py
src/RSIPI/static_plotter.py
src/RSIPI/timing_metrics.py
src/RSIPI/tools_api.py
src/RSIPI/trajectory_planner.py
src/RSIPI/viz_api.py
src/RSIPI/xml_handler.py
src/RSIPI.egg-info/PKG-INFO
src/RSIPI.egg-info/SOURCES.txt
src/RSIPI.egg-info/dependency_links.txt
src/RSIPI.egg-info/requires.txt
src/RSIPI.egg-info/top_level.txt
tests/test_safety_manager.py
tests/test_trajectory_planner.py
tests/test_xml_handler.py

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pandas>=2.0
numpy>=1.22
matplotlib>=3.5
lxml>=4.9
scipy>=1.8
[dev]
pytest>=7.0

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RSIPI