Beyond Task and Motion Planning: Hierarchical Robot Planning with General-Purpose Policies

• URL: http://arxiv.org/abs/2504.17901v1
• Date: Thu, 24 Apr 2025 19:22:50 GMT
• Title: Beyond Task and Motion Planning: Hierarchical Robot Planning with General-Purpose Policies
• Authors: Benned Hedegaard, Ziyi Yang, Yichen Wei, Ahmed Jaafar, Stefanie Tellex, George Konidaris, Naman Shah,
• Abstract summary: We address the challenge of planning with both kinematic skills and closed-loop motor controllers.<n>We propose a novel method that integrates these controllers into motion planning using Composable Interaction Primitives.
• Score: 32.85839714467011
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Task and motion planning is a well-established approach for solving long-horizon robot planning problems. However, traditional methods assume that each task-level robot action, or skill, can be reduced to kinematic motion planning. In this work, we address the challenge of planning with both kinematic skills and closed-loop motor controllers that go beyond kinematic considerations. We propose a novel method that integrates these controllers into motion planning using Composable Interaction Primitives (CIPs), enabling the use of diverse, non-composable pre-learned skills in hierarchical robot planning. Toward validating our Task and Skill Planning (TASP) approach, we describe ongoing robot experiments in real-world scenarios designed to demonstrate how CIPs can allow a mobile manipulator robot to effectively combine motion planning with general-purpose skills to accomplish complex tasks.

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