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Human-robot interaction requires explicit reasoning on human environment and on robot capacities to achieve its tasks in a collaborative way with a human partner. We have devised a decisional framework for humanrobot interactive task achievement that is aimed to allow the robot not only to accomplish its tasks but also to produce behaviors that support its engagement vis-avis its human partner and to interpret human behaviors and intentions.

Together and in coherence with this framework, we intend to develop and experiment various task planners and interaction schemes that will allow the robot to select and perform its tasks while taking into account explicitly the human abilities as well as the constraints imposed by the presence of humans, their needs and preferences. We present the first results obtained by our “human-aware” task and motion planners and discuss how they can be extended.