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Course Outline
Introduction to Safety and Explainability in Robotics
- Overview of safety and transparency principles in robotic systems
- The 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 design
Verification and Validation Techniques
- Testing robotic behaviors in simulated environments
- Implementing formal verification and designing test cases
- Utilizing data-driven validation and monitoring methods
Safety Case Development
- Structuring and defining the content of a safety case
- Documenting compliance and ensuring traceability
- Utilizing tools for evidence management and risk justification
Explainable AI for Robotics
- Ensuring transparency in decision-making processes
- Applying interpretability techniques to ML-based control systems
- Communicating robotic behaviors 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
Hands-On Workshop: Building 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
Summary and Next Steps
Requirements
- A foundational understanding of robotics systems and control architectures
- Proficiency with Python programming and simulation tools
- Knowledge of system engineering or safety processes
Target Audience
- System engineers engaged in robotics or autonomous system development
- Safety officers responsible for ensuring compliance with functional safety standards
- Technical managers overseeing 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.