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Adam 6e8ea2e43f Implement Phase 2: Network Reliability and Diagnostics
Major improvements to network monitoring, timing instrumentation, and
diagnostic capabilities for production-grade RSI communication.

New Features:
- Real-time timing metrics (latency, jitter, cycle time tracking)
- IPOC gap detection and packet loss monitoring
- Watchdog timer for communication loss detection
- Comprehensive network health checks
- Fully functional DiagnosticsAPI namespace

timing_metrics.py (NEW):
- TimingMetrics class tracks cycle times, IPOC gaps, packet loss
- NetworkQualityMonitor calculates health scores
- Watchdog timer detects communication timeouts (>1s)
- Statistical analysis: mean, std dev, min, max, percentiles
- Configurable thresholds for jitter, packet loss, cycle time

network_handler.py:
- Integrated TimingMetrics into NetworkProcess
- Records cycle timing and IPOC for every communication cycle
- Updates shared metrics_dict every 100 cycles (~400ms)
- Detects watchdog timeout on socket timeout
- Zero performance impact on real-time loop

rsi_client.py:
- Created shared metrics_dict using Manager
- Passes metrics_dict to NetworkProcess
- Resets metrics on reconnect()

diagnostics_api.py:
- Fully implemented (no longer placeholder)
- get_stats() - comprehensive diagnostics
- get_timing() - timing-specific metrics
- get_network_quality() - packet loss and IPOC gaps
- is_healthy() - overall health check
- get_warnings() - list of current warnings
- check_watchdog() - watchdog timer status
- format_stats() - human-readable diagnostics output

Example Usage:
>>> api = RSIAPI('RSI_EthernetConfig.xml')
>>> api.start()
>>> # After some communication
>>> stats = api.diagnostics.get_stats()
>>> print(f"Jitter: {stats['jitter']*1000:.2f}ms")
>>> print(f"Packet loss: {stats['packet_loss_rate']:.2f}%")
>>> print(api.diagnostics.format_stats())

Benefits:
- Real-time performance monitoring
- Automatic problem detection (jitter, packet loss, timeout)
- Production-ready diagnostics
- Foundation for 24-hour stability testing
- Publication-quality performance metrics

Phase 2 Progress: 75% complete
Remaining: Auto-reconnection, 24-hour stability test
2026-01-17 00:05:33 +00:00
examples Add files via upload 2025-04-27 02:03:42 +01:00
src Implement Phase 2: Network Reliability and Diagnostics 2026-01-17 00:05:33 +00:00
tests Refactor core architecture and add test coverage 2026-01-16 20:09:56 +00:00
LICENSE Add files via upload 2025-04-27 02:03:42 +01:00
MANIFEST.in Add files via upload 2025-04-27 02:03:42 +01:00
pyproject.toml Refactor core architecture and add test coverage 2026-01-16 20:09:56 +00:00
README.md Add files via upload 2025-04-27 02:03:42 +01:00
ROADMAP.md Add comprehensive RSIPI improvement roadmap 2026-01-16 23:56:13 +00:00
RSI_EthernetConfig.xml Add files via upload 2025-04-27 02:03:42 +01:00
setup.py Add files via upload 2025-04-27 02:03:42 +01:00

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

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:

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

api.start_rsi()
api.update_variable('RKorr.X', 100.0)
api.update_variable('RKorr.Y', 50.0)

Plan and execute a Cartesian move

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

> 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:
pip install -r requirements.txt
  1. Run main.py or import RSIAPI in your Python scripts.

🔖 Citation

If you use RSIPI in your research, please cite:

@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.