Abstract
Mobile manipulators installed in warehouses and factories for conveying goods between working stations need to meet the requirements of time-critical workflows. Moreover, the systems are expected to deal with changing tasks, cluttered environments and constraints imposed by the goods to be delivered. In this paper, we present a novel planning framework for generating asymptotically optimal paths for mobile manipulators subject to task constraints. Our approach introduces the Bidirectional Informed RRT* (BI2RRT*) that extends the Informed RRT* [1] towards bidirectional search and satisfaction of end-effector task constraints. In various experiments, we demonstrate the efficiency of BI2RRT* for both unconstrained and constrained mobile manipulation planning problems. As the results show, our planning framework finds better solutions than Informed RRT* and Bidirectional RRT* in less planning.
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