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Course Outline
Foundations of Safety and Explainability in Robotics
- An overview of safety and transparency within 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 hazards in autonomous and semi-autonomous systems
- Conducting Failure Mode and Effects Analysis (FMEA)
- Quantifying risk and implementing mitigation through safety-centric design
Verification and Validation Techniques
- Testing robotic behaviours in simulated environments
- Formal verification and the design of test cases
- Data-driven validation and continuous monitoring strategies
Developing the Safety Case
- Structuring and defining the content of a safety case
- Documenting compliance and ensuring traceability
- Utilising tools for evidence management and risk justification
Explainable AI in Robotics
- Ensuring transparency in decision-making processes
- Interpretability techniques for ML-based control systems
- Explaining robotic behaviours to end-users and regulatory bodies
Ethical and Governance Considerations
- 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 Explainable Robotics Scenario
- Designing a basic robotic simulation using ROS 2 or Gazebo
- Applying verification and validation procedures
- Developing and presenting a summary of the safety case
Conclusion and Path Forward
Requirements
- A fundamental grasp of robotics systems and control architectures
- Proficiency in Python programming and simulation tools
- Insight into system engineering or safety processes
Target Audience
- System engineers involved in robotics or autonomous system development
- Safety officers tasked with ensuring adherence to 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.
