Monitoring the execution of robot plans using semantic knowledge
Robotics and Autonomous Systems
Context-based design of robotic systems
Robotics and Autonomous Systems
Monitoring the Execution of a Multi-Agent Plan: Dealing with Partial Observability
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
PDDL2.1: an extension to PDDL for expressing temporal planning domains
Journal of Artificial Intelligence Research
Chronicle recognition improvement using temporal focusing and hierarchization
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A distributed control loop for autonomous recovery in a multi-agent plan
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Bridging control and artificial intelligence theories for diagnosis: A survey
Engineering Applications of Artificial Intelligence
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The paper addresses the problem of supervising the execution of a plan with durative actions in a just partially known world, where discrepancies between the expected conditions and the ones actually found may arise. The paper advocates a control architecture which exploits additional knowledge to prevent (when possible) action failures by changing the execution modality of actions while these are still in progress. Preliminary experimental results, obtained in a simulated space exploration scenario, are reported.