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Course Outline
Introduction to Safety and Explainability in Robotics
- Perspective on safety and transparency within 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 levels and implementing mitigation strategies through safety design
Verification and Validation Techniques
- Evaluating robotic behaviors within simulated environments
- Applying formal verification methods and designing test cases
- Utilizing data-driven validation and monitoring approaches
Safety Case Development
- Structuring and defining the content of a safety case
- Recording compliance details and ensuring traceability
- Leveraging tools for evidence management and risk justification
Explainable AI for Robotics
- Enhancing the transparency of decision-making processes
- Employing interpretability techniques for ML-based control systems
- Communicating robotic behaviors to users and regulatory bodies
Ethical and Governance Considerations
- Exploring ethical principles in robotics and autonomous systems
- Addressing bias, accountability, and responsibility in AI-driven robotics
- Striking a balance between innovation and public trust alongside regulation
Practical Workshop: Creating a Safe and Explainable Robotics Scenario
- Configuring a compact robotic simulation using ROS 2 or Gazebo
- Executing verification and validation procedures
- Formulating and presenting a summary of the safety case
Conclusion and Future Directions
Requirements
- Fundamental comprehension of robotics systems and control architectures
- Proficiency with Python programming and simulation tools
- Background knowledge in system engineering or safety processes
Target Audience
- System engineers specializing in robotics or autonomous systems
- Safety professionals focused on adhering to functional safety standards
- Technical managers responsible for 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.