Realization of task intelligence for service robots in an unstructured environment.

Annual Reviews in Control(2017)

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摘要
In order to perform various tasks using a robot in a real environment, it is necessary to learn the tasks based on recognition, to be able to derive a task sequence suitable for the situation, and to be able to generate a behavior adaptively. To deal with this issue, this paper proposes a system for realizing task intelligence having a memory module motivated by human episodic memory, and a task planning module to resolve the current situation. In addition, this paper proposes a technique that can modify demonstrated trajectories according to current robot states and recognized target positions in order to perform the determined task sequence, as well as a technique that can generate the modified trajectory without collisions with surrounding obstacles. The effectiveness and applicability of the task intelligence are demonstrated through experiments with Mybot, a humanoid robot developed in the Robot Intelligence Technology Laboratory at KAIST.
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关键词
Task intelligence,Episodic memory,Deep ART network,Motion planning,Task planner
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