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Course Outline
Foundations of Safety and Explainability in Robotics
- Overview of safety and transparency principles 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 risks and implementing mitigation through safety-driven design
Verification and Validation Techniques
- Testing robotic behaviours within simulated environments
- Implementing formal verification and designing test cases
- Utilising data-driven validation and monitoring methods
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 behaviours to users and regulatory bodies
Ethical and Governance Considerations
- Core ethical principles in robotics and autonomous systems
- Addressing bias, accountability, and responsibility in AI-driven robotics
- Balancing innovation with public trust and regulatory requirements
Practical Workshop: Creating a Safe and Explainable Robotics Scenario
- Designing a small robotic simulation using ROS 2 or Gazebo
- Applying verification and validation procedures
- Developing and presenting a summary of the safety case
Wrap-up and Future Steps
Requirements
- Foundational knowledge of robotics systems and control architectures
- Proficiency with Python programming and simulation tools
- Understanding of system engineering or safety processes
Target Audience
- System engineers involved in robotics or autonomous systems
- Safety officers responsible for compliance with functional safety standards
- Technical managers supervising robotics integration and deployment
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.
