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Duration 21 hours
Course Outline
Foundations of Safety and Interpretability in Robotics
- Overview of safety and transparency 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 Assessment
- Identifying potential hazards in autonomous and semi-autonomous systems
- Conducting Failure Mode and Effects Analysis (FMEA)
- Quantifying risk and implementing mitigations through safety design
Validation and Verification Methods
- Testing robotic behaviors in simulated environments
- Formal verification and test case development
- Data-driven validation and monitoring approaches
Safety Case Formulation
- Structuring and defining the content of a safety case
- Documenting compliance and traceability
- Utilizing tools for evidence management and risk justification
Interpretable AI in Robotics
- Enhancing the transparency of decision-making processes
- Interpretability techniques for ML-based control systems
- Communicating robotic behaviors to end-users and regulatory bodies
Ethical and Governance Dimensions
- Ethical principles governing robotics and autonomous systems
- Bias, accountability, and responsibility in AI-driven robotics
- Balancing innovation with public trust and regulatory requirements
Practical Workshop: Creating a Safe and Interpretable Robotics Scenario
- Designing a small robotic simulation using ROS 2 or Gazebo
- Applying validation and verification procedures
- Developing and presenting a safety case summary
Conclusion and Future Steps
Requirements
- Foundational knowledge of robotic systems and control architectures
- Proficiency with Python programming and simulation software
- Understanding of systems engineering or safety processes
Target Audience
- Systems engineers engaged in robotics or autonomous systems projects
- Safety specialists responsible for adhering to functional safety standards
- Technical managers supervising robotic integration and rollout
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.