Safeware: system safety and computers
Safeware: system safety and computers
Cambrian intelligence: the early history of the new AI
Cambrian intelligence: the early history of the new AI
Intelligent systems for engineers and scientists (2nd ed.)
Intelligent systems for engineers and scientists (2nd ed.)
Towards integrated safety analysis and design
ACM SIGAPP Applied Computing Review - Special issue on saftey-critical software
Safety Critical Computer Systems
Safety Critical Computer Systems
Developing artificial neural networks for safety critical systems
Neural Computing and Applications
Pre-collision safety strategies for human-robot interaction
Autonomous Robots
Human-robot interaction: a survey
Foundations and Trends in Human-Computer Interaction
Robotic Home Assistant Care-O-bot® 3 Product Vision and Innovation Platform
Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques
Risk management simulator for low-powered human-collaborative industrial robots
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A Novel HAZOP study approach in the RAMS analysis of a therapeutic robot for disabled children
SAFECOMP'10 Proceedings of the 29th international conference on Computer safety, reliability, and security
MODIFI: a MODel-implemented fault injection tool
SAFECOMP'10 Proceedings of the 29th international conference on Computer safety, reliability, and security
Biomimetics: Nature-Based Innovation
Biomimetics: Nature-Based Innovation
A UML-based method for risk analysis of human-robot interactions
Proceedings of the 2nd International Workshop on Software Engineering for Resilient Systems
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In recent years there has been a concerted effort to address many of the safety issues associated with physical human-robot interaction (pHRI). However, a number of challenges remain. For personal robots, and those intended to operate in unstructured environments, the problem of safety is compounded. In this paper we argue that traditional system design techniques fail to capture the complexities associated with dynamic environments. We present an overview of our safety-driven control system and its implementation methodology. The methodology builds on traditional functional hazard analysis, with the addition of processes aimed at improving the safety of autonomous personal robots. This will be achieved with the use of a safety system developed during the hazard analysis stage. This safety system, called the safety protection system, will initially be used to verify that safety constraints, identified during hazard analysis, have been implemented appropriately. Subsequently it will serve as a high-level safety enforcer, by governing the actions of the robot and preventing the control layer from performing unsafe operations. To demonstrate the effectiveness of the design, a series of experiments have been conducted using a MobileRobots PeopleBot. Finally, results are presented demonstrating how faults injected into a controller can be consistently identified and handled by the safety protection system.