TopAY: Efficient Trajectory Planning for Differential Drive Mobile Manipulators via Topological Paths Search and Arc Length-Yaw Parameterization

TL;DR

TopAY is a novel optimization-based framework that efficiently plans safe trajectories for differential drive mobile manipulators by combining topological path search and arc length-yaw parameterization, outperforming existing methods.

Contribution

It introduces a hierarchical planning strategy with topological path search and polynomial trajectory representation tailored for nonholonomic mobile manipulators.

Findings

Higher planning efficiency in dense scenarios

Increased success rates over state-of-the-art methods

Validated through extensive simulations and real-world tests

Abstract

Differential drive mobile manipulators combine the mobility of wheeled bases with the manipulation capability of multi-joint arms, enabling versatile applications but posing considerable challenges for trajectory planning due to their high-dimensional state space and nonholonomic constraints. This paper introduces TopAY, an optimization-based planning framework designed for efficient and safe trajectory generation for differential drive mobile manipulators. The framework employs a hierarchical initial value acquisition strategy, including topological paths search for the base and parallel sampling for the manipulator. A polynomial trajectory representation with arc length-yaw parameterization is also proposed to reduce optimization complexity while preserving dynamic feasibility. Extensive simulation and real-world experiments validate that TopAY achieves higher planning efficiency and success rates than state-of-the-art method in dense and complex scenarios. The source code is released at https://github.com/TopAY-Planner/TopAY .