Task Allocation for Multi-Robot Task and Motion Planning: a case for Object Picking in Cluttered Workspaces

• URL: http://arxiv.org/abs/2110.04089v1
• Date: Fri, 8 Oct 2021 12:36:43 GMT
• Title: Task Allocation for Multi-Robot Task and Motion Planning: a case for Object Picking in Cluttered Workspaces
• Authors: Hossein Karami, Antony Thomas, Fulvio Mastrogiovanni
• Abstract summary: We present an integrated multi-robot task and motion planning approach. It is capable of handling tasks which involve an unknown number of object re-arrangements. We demonstrate our results with experiments in simulation on two Franka Emika manipulators.
• Score: 1.3535770763481902
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present an AND/OR graph-based, integrated multi-robot task and motion planning approach which (i) performs task allocation coordinating the activity of a given number of robots, and (ii) is capable of handling tasks which involve an a priori unknown number of object re-arrangements, such as those involved in retrieving objects from cluttered workspaces. Such situations may arise, for example, in search and rescue scenarios, while locating/picking a cluttered object of interest. The corresponding problem falls under the category of planning in clutter. One of the challenges while planning in clutter is that the number of object re-arrangements required to pick the target object is not known beforehand, in general. Moreover, such tasks can be decomposed in a variety of ways, since different cluttering object re-arrangements are possible to reach the target object. In our approach, task allocation and decomposition is achieved by maximizing a combined utility function. The allocated tasks are performed by an integrated task and motion planner, which is robust to the requirement of an unknown number of re-arrangement tasks. We demonstrate our results with experiments in simulation on two Franka Emika manipulators.

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