Task and Motion Planning for Humanoid Loco-manipulation

TL;DR

This paper introduces an optimization-based framework for integrated task and motion planning in humanoid robots, enabling complex loco-manipulation behaviors by unifying contact mode planning with whole-body dynamics.

Contribution

It presents the first integrated TAMP approach that combines acyclic planning, contact mode representation, and whole-body dynamics for humanoid loco-manipulation.

Findings

Successfully generates complex loco-manipulation behaviors.

Handles long action sequences with physical consistency.

Unifies high-level planning with low-level motion constraints.

Abstract

This work presents an optimization-based task and motion planning (TAMP) framework that unifies planning for locomotion and manipulation through a shared representation of contact modes. We define symbolic actions as contact mode changes, grounding high-level planning in low-level motion. This enables a unified search that spans task, contact, and motion planning while incorporating whole-body dynamics, as well as all constraints between the robot, the manipulated object, and the environment. Results on a humanoid platform show that our method can generate a broad range of physically consistent loco-manipulation behaviors over long action sequences requiring complex reasoning. To the best of our knowledge, this is the first work that enables the resolution of an integrated TAMP formulation with fully acyclic planning and whole body dynamics with actuation constraints for the humanoid loco-manipulation problem.