MoboTSP: Solving the Task Sequencing Problem for Mobile Manipulators

TL;DR

This paper presents MoboTSP, a novel method for mobile manipulator task sequencing that uses geometric and optimization techniques to improve efficiency and generality over existing approaches.

Contribution

It introduces a new clustering-based approach for task sequencing that is more general and computationally efficient than prior methods.

Findings

Reduces base movements and execution time.

Provides a principled segmentation and sequencing method.

Outperforms existing approaches in efficiency and generality.

Abstract

We introduce a new approach to tackle the mobile manipulator task sequencing problem. We leverage computational geometry, graph theory and combinatorial optimization to yield a principled method to segment the task-space targets into clusters, analytically determine reachable base pose for each cluster, and find task sequences that minimize the number of base movements and robot execution time. By clustering targets first and by doing so from first principles, our solution is more general and computationally efficient when compared to existing methods.