面向抓取任务的移动机器人停靠位置优化方法研究

王东; 黄瑞元; 李伟政; 黄之峰

doi:10.12052/gdutxb.200165

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面向抓取任务的移动机器人停靠位置优化方法研究

更新时间：2026-05-27

- 面向抓取任务的移动机器人停靠位置优化方法研究
- A Research on Docking Position Optimization Method of Mobile Robot for Grasping Task
- 广东工业大学学报 2021年38卷第6期页码：53-61
- 作者机构：
  
  广东工业大学自动化学院,广东,广州,510006
- 作者简介：
  
  王东(1997–)，男，硕士研究生，主要研究方向为移动机械臂
  黄之峰(1984–)，男，副教授，博士，主要研究方向为仿人机器人、柔顺关节机器人，E-mail：zhifeng@gdut.edu.cn
- 基金信息：
  
  国家自然科学基金青年科学基金资助项目(500160075);广东省自然科学基金资助博士启动项目(2016A030310350)
- DOI：10.12052/gdutxb.200165
  中图分类号： TP242.6;TP18
- 网络首发：2021-11-10，
  
  纸质出版：2021
- 稿件说明：
移动端阅览
王东, 黄瑞元, 李伟政, 黄之峰. 面向抓取任务的移动机器人停靠位置优化方法研究[J]. 广东工业大学学报, 2021, 38(6): 53-61.

Wang Dong, Huang Rui-yuan, Li Wei-zheng, et al. A Research on Docking Position Optimization Method of Mobile Robot for Grasping Task[J]. 2021, 38(6): 53-61.
王东, 黄瑞元, 李伟政, 黄之峰. 面向抓取任务的移动机器人停靠位置优化方法研究[J]. 广东工业大学学报, 2021, 38(6): 53-61. DOI： 10.12052/gdutxb.200165.

Wang Dong, Huang Rui-yuan, Li Wei-zheng, et al. A Research on Docking Position Optimization Method of Mobile Robot for Grasping Task[J]. 2021, 38(6): 53-61. DOI： 10.12052/gdutxb.200165.

摘要

为了解决移动机器人在复杂环境中物体抓取规划成功率低以及规划时间长等问题

本文提出了一种基于环境信息的预处理生成移动机器人停靠位置优化算法。首先对机械臂的工作空间进行分析

得到抓取难易评价标准

将环境中目标物、障碍物以及移动底盘位置简化为点

投影到

平面上

根据抓取难易评价标准求出移动机器人优化后的底盘停靠位置; 然后针对机械臂避障问题

采用快速扩展随机树(Rapidly-exploring Random Trees

RRT)算法实现了机械臂末端及连杆与障碍物的避障; 最后通过仿真和动作捕捉系统下的实验发现

采用移动机器人停靠位置优化算法可显著提高抓取规划成功率和规划速度。

Abstract

In order to solve the problems of low success rate and long planning time of mobile robot in complex environment

a mobile robot docking position optimization algorithm is proposed based on environment information preprocessing. Firstly

the workspace of the manipulator is analyzed

and the evaluation criteria of grasping difficulty are obtained. The positions of objects

obstacles and mobile chassis in the environment are simplified as points and projected on the

plane. According to the evaluation criteria of grasping difficulty

the optimized chassis docking position of the mobile robot is obtained. For the obstacle avoidance problem of the manipulator

the rapidly-exploring random trees (RRT) algorithm is used to realize the robot end

connecting rod and obstacle.

Finally

through the simulation and experiments in the motion capture system

it is found that using the parking position optimization algorithm of mobile robot can increase the success rate of grasping objects and the speed of grasping planning .

关键词

Keywords

references

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