Lazy Rearrangement Planning in Confined Spaces

• URL: http://arxiv.org/abs/2203.10379v1
• Date: Sat, 19 Mar 2022 18:59:43 GMT
• Title: Lazy Rearrangement Planning in Confined Spaces
• Abstract summary: This work introduces a lazy evaluation framework for object rearrangement in confined spaces. It improves upon a local monotone solver, which extends to a high-quality planner for the general, non-monotone case. It achieves high-quality solutions, i.e., only 1.8 additional actions on average are needed for non-monotone instances.
• Score: 14.38087412920014
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Object rearrangement is important for many applications but remains challenging, especially in confined spaces, such as shelves, where objects cannot be easily accessed from above and they block reachability to each other. Such constraints require many motion planning and collision checking calls, which are computationally expensive. In addition, the arrangement space (space of possible object placements) grows exponentially with the number of objects. To address these issues, this work introduces a lazy evaluation framework for object rearrangement in confined spaces. It improves upon a local monotone solver, which extends to a high-quality planner for the general, non-monotone case. Monotone instances are those that can be solved by moving each object at most once. A key insight is that reachability constraints at the grasps for objects' starts and goals can quickly reveal dependencies between objects without having to execute expensive motion planning queries. The local solver builds lazily a search tree that respects these reachability constraints without verifying that the arm paths are collision free. It only collision checks when a promising solution is found given grasp reachability. If a monotone solution is not found, the non-monotone planner loads the lazy search tree and explores ways to move objects to intermediate locations from where monotone solutions to the goal can be found. The non-monotone planner also applies lazy evaluation to minimize collision checking. Comprehensive simulations and robot demonstrations show that the proposed framework can solve difficult instances in confined spaces with up to 16 objects, which state-of-the-art methods fail to solve. It also achieves high-quality solutions, i.e., only 1.8 additional actions on average are needed for non-monotone instances. It also solves problems faster than alternatives, when the alternatives find a solution.

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