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.

翻译：我们考虑一系列具有挑战性的序列操作谜题，其中智能体必须与多个可移动物体交互并穿越狭窄通道。这类场景对于任务与运动规划器而言极为困难，因为它们需要相互依赖的重新抓取操作并解决复杂的运动规划问题。本文提出通过搜索更简单的拾取与放置子问题序列，从而找到操作谜题的解决方案。我们的方法将启发式引导的子问题前向搜索与基于优化的任务与运动规划求解器相结合。为引导搜索过程，我们引入启发式规则来生成并优先排序有用的子目标。我们在多种人工设计和自动生成的场景中评估该方法，证明了辅助子问题在序列操作规划中的优势。