基于铁塔模型和双向天牛须的改进RRT轨迹规划方法
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合肥工业大学电气与自动化工程学院

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中图分类号:

TP273

基金项目:

国家自然科学基金项目(62073113,62003122),安徽省自然科学基金(2008085UD03)


Improved RRT Trajectory Planning Method Based on Tower Model and Two-way BAS
Author:
Affiliation:

1.Hefei University of Technology School of Electrical Engineering and Automation;2.School of Electrical Engineering and Automation Hefei University of Technology

Fund Project:

the National Natural Science Foundation of China under Grants No.62073113, No.62003122, and the Natural Science Foundation of Anhui Province under Grants No. 2208085UD03.

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    摘要:

    为了提高输电铁塔高空作业自动化水平和保障高空作业机器人设备安全,针对传统RRT和A*等算法在角钢塔高空复杂环境中无法快速规划机械臂安全轨迹的问题,提出一种基于铁塔模型的双向天牛须知情快速随机扩展树轨迹规划算法(BAS-InformedRRT*Connect,BI-RRT*Connect)。首先数字重构高空机器人作业环境,利用模型配准方法,获取输电铁塔精准模型信息,接着根据铁塔模型寻求机械臂末端点和作业目标之间的可行路径,并添加天牛须算法改进随机采样过程,采用两只天牛相互寻找快速获取初始路径解,最后将初始路径作为先验知识构建椭圆体采样区域以优化路径。在Unity环境下搭建实验平台将所提算法与RRT和A*等四种传统算法进行比较,实验结果表明,该算法在输电铁塔多种作业区域下都具有求解速度快,求解质量高的良好效果。

    Abstract:

    In order to improve the automation level of high-altitude operation of transmission tower and ensure the safety of high-altitude operation robot equipment, aiming at the problem that traditional RRT and A * algorithms cannot quickly plan the safe trajectory of manipulator in high-altitude complex environment of angle steel tower, a two-way beetle informed rapid random expansion tree trajectory planning algorithm ( BAS-Informed RRT * Connect, BI-RRT * Connect ) based on tower model is proposed. Firstly, the working environment of the high-altitude robot is reconstructed digitally, and the accurate model information of the transmission tower is obtained by using the model registration method. Then, according to the tower model, the feasible path between the end point of the manipulator and the working target is sought, and the beetle antennae algorithm is added to improve the random sampling process. Two beetles are used to find each other to quickly obtain the initial path solution. Finally, the initial path is used as a priori knowledge to construct the optimal path of the elliptical sampling area. The experimental platform is built in Unity environment to compare the proposed algorithm with four traditional algorithms such as RRT and A *. The experimental results show that the algorithm has fast solution speed and high solution quality in various operation areas of transmission tower.

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  • 收稿日期:2024-03-31
  • 最后修改日期:2024-08-19
  • 录用日期:2024-08-19
  • 在线发布日期: 2024-08-31
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