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Course Outline
Introduction to Safety and Explainability in Robotics
- Overview of safety and transparency within robotic systems
- Regulatory and ethical landscape for robotics and AI
- Relevant standards and frameworks: ISO 26262, ISO 10218, and ISO/IEC 42001
Risk and Hazard Analysis
- Identification of 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
- Assessing robotic behaviors within simulated environments
- Applying formal verification and designing test cases
- Employing data-driven validation and monitoring methods
Safety Case Development
- Structuring and defining the content of a safety case
- Documenting compliance and maintaining traceability
- Utilizing 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 clearly to users and regulators
Ethical and Governance Considerations
- Application of ethical principles in robotics and autonomous systems
- Managing bias, accountability, and responsibility in AI-driven robotics
- Striking a balance between innovation, public trust, and regulation
Hands-On Workshop: Building a Safe and Explainable Robotics Scenario
- Creating a small-scale robotic simulation using ROS 2 or Gazebo
- Executing verification and validation procedures
- Developing and presenting a summary of the safety case
Summary and Next Steps
Requirements
- Fundamental understanding of robotics systems and control architectures
- Proficiency in Python programming and simulation tools
- Knowledge of system engineering or safety processes
Target Audience
- System engineers engaged in robotics or autonomous systems
- Safety officers responsible for ensuring 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.
