Efficient Task Planning for Mobile Manipulation: a Virtual Kinematic Chain Perspective

TL;DR

This paper introduces a Virtual Kinematic Chain (VKC) perspective that simplifies task planning for mobile manipulation by consolidating kinematics, reducing search space, and improving planning efficiency and feasibility.

Contribution

The paper proposes a novel VKC perspective that enhances task planning efficiency and feasibility in mobile manipulation by simplifying domain definitions and reducing search complexity.

Findings

VKC-based domain reduces planning time and memory usage.

Abstract actions improve feasibility of motion plans.

VKC approach scales well to complex tasks.

Abstract

We present a Virtual Kinematic Chain (VKC) perspective, a simple yet effective method, to improve task planning efficacy for mobile manipulation. By consolidating the kinematics of the mobile base, the arm, and the object being manipulated collectively as a whole, this novel VKC perspective naturally defines abstract actions and eliminates unnecessary predicates in describing intermediate poses. As a result, these advantages simplify the design of the planning domain and significantly reduce the search space and branching factors in solving planning problems. In experiments, we implement a task planner using Planning Domain Definition Language (PDDL) with VKC. Compared with conventional domain definition, our VKC-based domain definition is more efficient in both planning time and memory. In addition, abstract actions perform better in producing feasible motion plans and trajectories. We further scale up the VKC-based task planner in complex mobile manipulation tasks. Taken together, these results demonstrate that task planning using VKC for mobile manipulation is not only natural and effective but also introduces new capabilities.