Abstract
The present paper proposes global quasi-static manipulation planning for the whole arm manipulation with a planar hand system and environments. The manipulation planning becomes complex since the changes of contact states between objects and hand/environments occur very frequently during the manipulation. In addition, a search space is expressed as a hybrid system which consists of time-continuous and discrete systems including motion states and contact states, respectively. To overcome those problems, a novel randomized algorithm is applied to the manipulation planning. The proposed planning generates a contact state network which connects the initial and goal configurations by expanding subgoals in the search space based on forward problem approaches. The validity of the proposed planning is shown by simulations.
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