Contact States Detection for Dexterous Manipulation in Low-Dimensional Joint Space
نویسندگان
چکیده
Contact state is an important element in teaching robot to manipulate an object in Learning from Observation paradigm. Contact between hand and object is changed during dexterous manipulation, and these changes are difficult to detect. An alternative approach for discovering this information is proposed by considering contact states in a human hand movement. A main contribution of this study is a segmentation method for human manipulative movement. Human manipulative movement can be segmented by considering a low-dimensional joint space. The proposed method successfully divides human movement into many short movements where, within the same movement, contact state is consistent.
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