Solving Sequential Manipulation Puzzles by Finding Easier Subproblems

TL;DR

This paper introduces a novel approach for solving complex sequential manipulation puzzles by decomposing them into easier subproblems, combining heuristic search with optimization-based planning to improve success rates.

Contribution

It presents a method that searches over sequences of simpler pick-and-place subproblems, guided by heuristics, to solve challenging manipulation puzzles more effectively.

Findings

Improved success rates on complex manipulation scenes

Effective guidance of subproblem search via heuristics

Demonstrated benefits of auxiliary subproblems in planning

Abstract

We consider a set of challenging sequential manipulation puzzles, where an agent has to interact with multiple movable objects and navigate narrow passages. Such settings are notoriously difficult for Task-and-Motion Planners, as they require interdependent regrasps and solving hard motion planning problems. In this paper, we propose to search over sequences of easier pick-and-place subproblems, which can lead to the solution of the manipulation puzzle. Our method combines a heuristic-driven forward search of subproblems with an optimization-based Task-and-Motion Planning solver. To guide the search, we introduce heuristics to generate and prioritize useful subgoals. We evaluate our approach on various manually designed and automatically generated scenes, demonstrating the benefits of auxiliary subproblems in sequential manipulation planning.