Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Foundations of Safety and Interpretability in Robotics
- An overview of safety and transparency principles in robotic systems
- The regulatory and ethical landscape for robotics and AI
- Key standards and frameworks, including ISO 26262, ISO 10218, and ISO/IEC 42001
Risk and Hazard Assessment
- Identifying potential hazards in autonomous and semi-autonomous systems
- Conducting Failure Mode and Effects Analysis (FMEA)
- Quantifying risks and implementing mitigations through safety-driven design
Verification and Validation Methodologies
- Testing robotic behaviors within simulated environments
- Applying formal verification and designing comprehensive test cases
- Utilizing data-driven validation and continuous monitoring techniques
Developing Safety Cases
- Structuring and defining the content of a safety case
- Documenting compliance evidence and ensuring traceability
- Leveraging 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
- Communicating robotic behaviors effectively to users and regulatory bodies
Ethical and Governance Perspectives
- Core ethical principles governing robotics and autonomous systems
- Addressing bias, accountability, and responsibility in AI-driven robotics
- Striking a balance between innovation, public trust, and regulatory requirements
Practical Workshop: Constructing a Safe and Interpretable Robotics Scenario
- Designing a small-scale robotic simulation using ROS 2 or Gazebo
- Applying verification and validation procedures
- Formulating 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 associated simulation tools
- An understanding of system engineering or established safety processes
Target Audience
- System engineers engaged in robotics or autonomous system development
- Safety officers responsible for adhering to functional safety standards
- Technical managers overseeing the integration and deployment of robotic solutions
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.