Abstract

We present a 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 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.

Demo

IROS21 Efficient Task Planning for Mobile Manipulation: a Virtual Kinematic Chain Perspective


Paper
Efficient Task Planning for Mobile Manipulation: a Virtual Kinematic Chain Perspective
Ziyuan Jiao*, Zeyu Zhang*, Weiqi Wang, David Han, Song-Chun Zhu, Yixin Zhu, Hangxin Liu
* Equal contributors
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021
Paper / Source Code / Video

Team

Bibtex

@inproceedings{jiao2021efficieint,
    title={Efficient Task Planning for Mobile Manipulation: a Virtual Kinematic Chain Perspective},
    author={Jiao, Ziyuan and Zeyu, Zhang and Wang, Weiqi and Han, David and Zhu, Song-Chun and Zhu, Yixin and Liu, Hangxin},
    booktitle={IROS},
    year={2021}
}