提出高效轨迹规划框架TopAY，解决差速移动机械臂的复杂路径生成难题。
TopAY: Efficient Trajectory Planning for Differential Drive Mobile Manipulators via Topological Paths Search and Arc Length-Yaw Parameterization
- 分层初始化：先搜拓扑路径，再并行采样机械臂配置
- 采用弧长-偏航参数化多项式表示，降低优化复杂度
- 在复杂场景中效率与成功率均优于现有方法
差速驱动移动机械臂结合了轮式底盘的机动性与多关节机械臂的操作能力，应用场景广泛，但其高维状态空间和非完整约束给轨迹规划带来巨大挑战。本文提出一种基于优化的规划框架TopAY，旨在实现高效且安全的轨迹生成。该框架采用分层初始值获取策略：先对底盘进行拓扑路径搜索，再对机械臂进行并行采样。同时提出一种基于弧长-偏航参数化的多项式轨迹表示方法，有效降低优化复杂度并保证动态可行性。大量仿真与真实世界实验表明，TopAY在密集复杂场景中相比最先进方法具有更高的规划效率和成功率。源代码已公开于 https://github.com/TopAY-Planner/TopAY。
原文摘要 · Abstract (English)
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 .
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