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室内动态环境下搬运机器人定位和自动避障算法研究

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本文针对搬运机器人定位和自动避障问题进行研究,利用FAST-LIO框架将激光雷达传感器和惯性测量单元多个传感器进行数据融合,实现对机器人位置和姿态的准确估计.基于蚁群算法和动态窗口法提出了DWA-ACO的新型混合算法,以期对静态障碍物和动态障碍物进行实时避障,最后进行了仿真实验研究.仿真实验结果表明,本文提出的算法在定位和避障方面具有有效性和可行性.
Research on Algorithms of Moving Robot Localization and Automatic Obstacle Avoidance in Indoor Dynamic Environment
In this paper,the problem of localization and automatic obstacle avoidance of the moving robot is studied. The data fusion between the lidar sensor and the inertial measurement unit sensor is carried out using the FAST-LIO framework,the position and attitude of the robot can be estimated accurately. Based on ant colony algorithm and dynamic window method,a new hybrid algorithm of DWA-ACO is proposed to avoid static and dynamic obstacles in real time. The simulation results show that the proposed algorithm is effective and feasible in locating and avoiding obstacles.

moving robotFAST-LIOlocalization algorithmant colony algorithmdynamic window method

熊凌峰、洛艺榕、余佳、尤龙、李戈

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华新(佛山)彩色印刷有限公司,佛山 528000

浙江冠豪新材料有限公司,杭州 314200

北京印刷学院机电工程学院,北京102600

搬运机器人 FAST-LIO 定位算法 蚁群算法 动态窗口法

2024

北京印刷学院学报
北京印刷学院

北京印刷学院学报

影响因子:0.247
ISSN:1004-8626
年,卷(期):2024.32(8)