Towards the Safety of Human-in-the-Loop Robotics: Challenges and Opportunities for Safety Assurance of Robotic Co-Workers
arXiv:1404.2229 · doi:10.1109/ROMAN.2014.6926328
Abstract
The success of the human-robot co-worker team in a flexible manufacturing environment where robots learn from demonstration heavily relies on the correct and safe operation of the robot. How this can be achieved is a challenge that requires addressing both technical as well as human-centric research questions. In this paper we discuss the state of the art in safety assurance, existing as well as emerging standards in this area, and the need for new approaches to safety assurance in the context of learning machines. We then focus on robotic learning from demonstration, the challenges these techniques pose to safety assurance and indicate opportunities to integrate safety considerations into algorithms "by design". Finally, from a human-centric perspective, we stipulate that, to achieve high levels of safety and ultimately trust, the robotic co-worker must meet the innate expectations of the humans it works with. It is our aim to stimulate a discussion focused on the safety aspects of human-in-the-loop robotics, and to foster multidisciplinary collaboration to address the research challenges identified.
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- Effects of Faults, Experience, and Personality on Trust in a Robot Co-Worker
- Systematic and Realistic Testing in Simulation of Control Code for Robots in Collaborative Human-Robot Interactions
- Intelligent Agent-Based Stimulation for Testing Robotic Software in Human-Robot Interactions
- Coverage-Driven Verification - An approach to verify code for robots that directly interact with humans
- Model-Based Testing, Using Belief-Desire-Intentions Agents, of Control Code for Robots in Collaborative Human-Robot Interactions
- Model-based Test Generation for Robotic Software: Automata versus Belief-Desire-Intention Agents
- Safe Human-Interactive Control via Shielding
- Drivers' Manoeuvre Modelling and Prediction for Safe HRI