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Course Outline
Introduction to Safety and Explainability in Robotics
- Overview of safety and transparency concepts in robotic systems
- Regulatory and ethical landscape for robotics and AI
- Key standards and frameworks: ISO 26262, ISO 10218, and ISO/IEC 42001
Risk and Hazard Analysis
- Identifying potential hazards in autonomous and semi-autonomous systems
- Conducting Failure Mode and Effects Analysis (FMEA)
- Quantifying risk and implementing mitigation strategies through safety-focused design
Verification and Validation Techniques
- Testing robotic behaviors within simulated environments
- Applying formal verification and designing test cases
- Utilizing data-driven validation and monitoring approaches
Safety Case Development
- Structuring and defining the content of a safety case
- Documenting compliance and maintaining traceability
- Leveraging tools for evidence management and risk justification
Explainable AI for Robotics
- Enhancing the transparency of decision-making processes
- Applying interpretability techniques to ML-based control systems
- Communicating robotic behaviors to users and regulatory bodies
Ethical and Governance Considerations
- Ethical principles guiding robotics and autonomous systems
- Addressing bias, accountability, and responsibility in AI-driven robotics
- Balancing innovation with public trust and regulatory requirements
Hands-On Workshop: Constructing a Safe and Explainable Robotics Scenario
- Designing a compact robotic simulation using ROS 2 or Gazebo
- Executing verification and validation procedures
- Developing and presenting a summary of the safety case
Conclusion and Next Steps
Requirements
- Fundamental understanding of robotics systems and control architectures.
- Proficiency with Python programming and relevant simulation tools.
- Knowledge of system engineering principles or safety processes.
Target Audience
- System engineers specializing in robotics or autonomous systems.
- Safety officers responsible for ensuring compliance with functional safety standards.
- Technical managers overseeing the integration and deployment of robotics.
21 Hours
Testimonials (2)
Supply of the materials (virtual machine) to get straight into the excersises, and the explanation of the Ros2 core. Why things work a certain way.
Arjan Bakema
Course - Autonomous Navigation & SLAM with ROS 2
its knowledge and utilization of AI for Robotics in the Future.