🛡️ HaloSafe: ISO 15066 Safety Controller

HaloSafe is a high-integrity safety monitoring layer designed for collaborative robots (cobots). It implements Speed and Separation Monitoring (SSM) according to ISO/TS 15066 standards, serving as a "Man-in-the-Middle" compliance guard between motion planners and robot hardware.

📊 Safety Telemetry Dashboard (ISO 15066)

Real-time telemetry captured from the Admittance Controller during verified verification runs.

🟢 STATE: SAFE	🟡 STATE: WARN	🔴 STATE: STOP
Logic: Dist > max_dist	Logic: max > Dist > min	Logic: Dist < min_dist
Action: Full Velocity (100%)	Action: Dynamic Scaling	Action: Protective Stop (0%)

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🏗️ System Architecture

The system is architected as a closed-loop control system with a dedicated safety supervisor.

1. Admittance Controller (The Physics)

• Role: Simulates a Mass-Spring-Damper system ($M\ddot{x} + D\dot{x} + Kx = F_{ext}$).
• Function: Gives the robot "virtual weight," rendering it compliant to external forces (collisions) rather than rigid.
• Config: Managed via immutable PhysicsConfig dataclasses.

2. Safety Monitor (The Watchdog)

• Role: Implements the deterministic safety gates required by ISO 15066.
• Logic:
  • Green Zone (> 2.0m): 100% Velocity.
  • Yellow Zone (0.5m - 2.0m): Linear velocity scaling ($v_{safe} = v_{cmd} \times \alpha$).
  • Red Zone (< 0.5m): Hard Protective Stop (0% Velocity).

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✅ Quality Assurance & Verification

This repository adheres to strict Systems Engineering software standards to ensure reliability in safety-critical contexts.

Metric	Status	Standard
Static Analysis	10.00/10	Pylint (PEP 8 Strict)
Unit Testing	11/11 PASSED	unittest (Physics & Logic Coverage)
Runtime Safety	ACTIVE	Pre-flight Self-Checks on Boot
Architecture	PACE	Primary, Alternate, Contingency, Emergency Handling

Verification Protocol

The system includes a rigorous test suite (test_safety_controller.py) that validates:

1. Physics Integrity: Verifies $F=ma$ calculations and damping effects.
2. Boundary Analysis: Tests exact edge cases at 0.5m (Stop) and 2.0m (Free Run).
3. Fail-Safe Logic: Ensures system defaults to STOP state on invalid inputs.

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🚀 Usage

1. Run the Simulation

Launch the dashboard with real-time ASCII visualization:

python safety_controller.py

Note: The system performs a self-diagnostic pre-check before initializing the physics engine.

2. Run the Verification Suite

Execute the full unit test battery:

python test_safety_controller.py

🛠️ Configuration

System parameters are managed via frozen Dataclasses to prevent runtime mutation.

@dataclass(frozen=True)
class PhysicsConfig:
    mass: float = 5.0          # Virtual Mass (kg)
    damping: float = 10.0      # Virtual Damping (Ns/m)

@dataclass(frozen=True)
class SafetyConfig:
    min_dist: float = 0.5      # Red Zone: Protective Stop (m)
    max_dist: float = 2.0      # Green Zone: Full Speed (m)

📦 Dependencies

• Python 3.10+ (Required for Dataclasses)
• NumPy (Vector Math)

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Author: Charles Austin (Senior Systems Architect Refactor) Focus: Robotics Safety Systems, Human-Robot Interaction (HRI), Model-Based Systems Engineering