一种四阶段的快速移动机器人局部轨迹规划方法

doi:10.1007/s12204-022-2423-8

摘要/Abstract

摘要： 局部轨迹规划承担着移动机器人快速、平滑避障的功能，是评估移动机器人导航能力的主要指标之一。目前的方法把局部轨迹规划的各项要求表示成统一的问题进行求解，在计算能力受限时，基本上不能满足实时性。针对上述情况，本文提出了一种在低成本处理器上运行速度可以达到500 Hz的快速局部轨迹规划算法。把轨迹规划问题分为前端搜索和后端优化两个部分，其中前端搜索部分包括环境拓扑分析和图搜索，后端部分包括满足运动学约束的轨迹生成和最优轨迹的选取。与目前大多数方法不同，本文把轨迹规划问题分解成四个子模块，每一个子模块只考虑一个问题。通过四个子模块组合形成一个完整的规划算法，该算法快速地生成一条平滑、无碰撞的轨迹。实验证明提出的方法可以生成平滑且满足运动学约束的安全轨迹，并且有较快的规划速度。

关键词: 机器人，路径规划，轨迹生成，平滑轨迹规划

Abstract: Mobile robot local motion planning is responsible for the fast and smooth obstacle avoidance, which is one of the main indicators for evaluating mobile robots’ navigation capabilities. Current methods formulate local motion planning as a unified problem; therefore it cannot satisfy the real-time requirement on the platform with limited computing ability. In order to solve this problem, this paper proposes a fast local motion planning method that can reach a planning frequency of 500 Hz on a low-cost CPU. The proposed method decouples the local motion planning as the front-end path searching and the back-end optimization. The front-end is composed of the environment topology analysis and graph searching. The back-end includes dynamically feasible trajectory generation and optimal trajectory selection. Different from the popular methods, the proposed method decomposes the local motion planning into four sub-modules, each of which aims to solve one problem. Combining four submodules, the proposed method can obtain the complete local motion planning algorithm which can fast generate a smooth and collision-free trajectory. The experimental results demonstrate that the proposed method has the ability to obtain the smooth, dynamically feasible and collision-free trajectory and the speed of the planning is fast.

Key words: robotics, path planning, trajectory generation, smooth trajectory planning

中图分类号:

TP301.1

黄山1，黄洪钟1，曾奇2. 一种四阶段的快速移动机器人局部轨迹规划方法[J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 428-435.

HUANG Shan(黄山), HUANG Hongzhong(黄洪钟), ZENG Qi(曾奇). Fast Four-Stage Local Motion Planning Method for Mobile Robot[J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 428-435.

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