Efficient Task Planning for Mobile Manipulation: a Virtual Kinematic Chain Perspective
This work addresses task planning bottlenecks for mobile manipulation systems, offering incremental improvements in efficiency and scalability.
The paper tackles the problem of inefficient task planning for mobile manipulation by introducing a Virtual Kinematic Chain (VKC) perspective, which consolidates kinematics to simplify domain design and reduce search space, resulting in improved planning time, memory efficiency, and feasibility of motion plans.
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.