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
Introduction to Safety and Explainability in Robotics
- An overview of safety and transparency mechanisms in robotic systems
- The regulatory and ethical landscape governing 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 risk and implementing mitigation strategies through safety-centric design
Verification and Validation Techniques
- Testing robotic behaviours within simulated environments
- Employing formal verification methods and designing effective test cases
- Utilising data-driven validation and continuous monitoring techniques
Safety Case Development
- Understanding the structure and essential content of a safety case
- Documenting compliance and maintaining clear traceability
- Leveraging tools for evidence management and risk justification
Explainable AI for Robotics
- Enhancing transparency in decision-making processes
- Applying interpretability techniques to ML-based control systems
- Communicating robotic behaviours clearly to users and regulators
Ethical and Governance Considerations
- Core ethical principles in robotics and autonomous systems
- Addressing bias, accountability, and responsibility in AI-driven robotics
- Balancing technological innovation with public trust and regulatory requirements
Hands-On Workshop: Building a Safe and Explainable Robotics Scenario
- Designing a small-scale robotic simulation using ROS 2 or Gazebo
- Applying verification and validation procedures in practice
- Developing and presenting a concise safety case summary
Summary and Next Steps
Requirements
- A foundational understanding of robotics systems and control architectures
- Proficiency with Python programming and relevant simulation tools
- Familiarity with system engineering principles or established safety processes
Target Audience
- System engineers engaged in robotics or autonomous system development
- Safety officers responsible for ensuring compliance with functional safety standards
- Technical managers overseeing the integration and deployment of robotics 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.
