Planning in Inhabited Environments
Our work addresses issues related to the cohabitation of service robots and people in unstructured environments. We propose new planning techniques to empower robot means-end reasoning with the capability of taking into account human intentions and preferences. We also address the problem of human activity recognition in instrumented environments. We employ a constraint-based approach to realize a continuous inference process to attach a meaning to sensor traces as detected by sensors distributed in the environment.
KeywordsHuman-aware planning Human-robot interaction Planning under uncertainty Activity recognition Constraint-based planning
The work described in the thesis has been supported by CUGS (Swedish national computer science graduate school) and by the Swedish KK foundation. We are grateful to Lars Karlsson, Alessandro Saffiotti and Federico Pecora for their supervision and support. We also thank Dana Nau and Rachid Alami for the useful discussions and insightful advices.
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