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Course Outline
Foundations of Safety and Interpretability in Robotics
- An introduction to safety and transparency 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 Assessment
- Detecting hazards in autonomous and semi-autonomous systems
- Conducting Failure Mode and Effects Analysis (FMEA)
- Quantifying risk and implementing mitigation strategies through safety-focused design
Verification and Validation Approaches
- Assessing robotic behaviors within simulated settings
- Formal verification methods and the design of test cases
- Data-driven validation and ongoing monitoring strategies
Constructing a Safety Case
- The structure and essential elements of a safety case
- Recording compliance details and traceability
- Utilising tools for evidence management and risk justification
Explainable AI in Robotics
- Enhancing the transparency of decision-making processes
- Interpretability techniques for machine learning-based control systems
- Explaining robotic actions to end-users and regulatory bodies
Ethical and Governance Perspectives
- Ethical principles governing robotics and autonomous systems
- Addressing bias, accountability, and responsibility in AI-driven robotics
- Striking a balance between innovation, public confidence, and regulation
Practical Workshop: Creating a Safe and Interpretable Robotics Scenario
- Developing a basic robotic simulation using ROS 2 or Gazebo
- Implementing verification and validation procedures
- Drafting and presenting a summary of the safety case
Conclusion and Future Directions
Requirements
- A foundational grasp of robotic systems and control architectures
- Proficiency in Python programming and the use of simulation tools
- An understanding of system engineering or safety protocols
Intended Learners
- System engineers focused on robotics or autonomous platforms
- Safety professionals responsible for adhering to functional safety norms
- Technical leaders overseeing the integration and rollout of robotics
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.