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Course Outline
Foundations of Safety and Explainability in Robotics
- Exploring safety and transparency concepts 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 potential hazards in autonomous and semi-autonomous systems
- Conducting Failure Mode and Effects Analysis (FMEA)
- Quantifying risks and implementing mitigations through safety-focused design
Verification and Validation Methodologies
- Assessing robotic behaviors in simulated environments
- Applying formal verification and designing robust test cases
- Utilizing data-driven validation and monitoring strategies
Developing a Safety Case
- Structuring and defining the content of a safety case
- Documenting compliance and ensuring traceability
- Leveraging tools for evidence management and risk justification
Explainable AI in Robotics
- Enhancing the transparency of decision-making processes
- Applying interpretability techniques to ML-based control systems
- Communicating robotic behaviors to end-users and regulatory bodies
Ethical and Governance Perspectives
- Core ethical principles in robotics and autonomous systems
- Addressing bias, accountability, and responsibility in AI-driven robotics
- Striking a balance between innovation, public trust, and regulation
Practical Workshop: Constructing a Safe and Explainable Robotics Scenario
- Creating a small-scale robotic simulation using ROS 2 or Gazebo
- Implementing verification and validation procedures
- Formulating and presenting a concise safety case summary
Conclusion and Pathways Forward
Requirements
- Fundamental understanding of robotic systems and control architectures
- Working familiarity with Python programming and simulation tools
- Proficiency in system engineering or safety management processes
Target Audience
- System engineers developing robotics or autonomous systems
- Safety professionals responsible for functional safety standard compliance
- 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.