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基于激光SLAM多地形机器人的设计 被引量:1

Design of Multi-terrain Robot Based on Laser SLAM
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摘要 为解决传统轮式机器人在复杂地形中受限与腿式机器人控制策略复杂的问题,提出一种多地形机器人。结合激光即时定位与地图构建(SLAM)方法和自适应式轮腿机构,将树莓派作为运算单元,搭载(ROS)机器人操作系统,应用激光SLAM技术实现环境地图构建和机器人导航,同时结合深度模型和摄像头完成图像任务。自适应式轮腿机械结构使机器人能够根据环境需求自动切换为轮式或腿式行进模式。底层控制器采用STM32F407,机器人通过PID算法能实现精准的移动和机械臂作业。结果表明:该多地形机器人控制方法简单高效,在坡地、草地、坑地、台阶障碍物等复杂地形中展现了灵活移动的能力,最大翻越障碍高度可达250 mm,爬坡角度可达45°,在稳定性和适应性方面具有显著优势。 In order to solve the problem of traditional wheeled robots in complex terrains and the complexity of control strategies in legged robots,a multi-terrain robot is proposed.Combining the laser simultaneous localization and mapping(SLAM)method and the adaptive legwheel mechanism,a Raspberry Pi serves is used as the computational unit with robot operating system(ROS),the laser SLAM technology is used to realize the environment map construction and the robot navigation,while combining the depth model and the camera to complete the image task.By using the adaptive wheel leg mechanical structure,the robot to automatically switch to wheel and legged modes can be enabled according to the environmental requirements.The STM32F407 is used as underlying controller,and the accurate movement and mechanical arm operation of the robot can be realized through the PID algorithm.The results show that the multi-terrain robot control method is simple and efficient,showing the ability of flexible movement in complex terrain such as slope,grassland,pit and step obstacles,the maximum height of the obstacle can reach 250 mm and the climbing angle can reach 45°,which has significant advantages in stability and adaptability.
作者 何冰 曾荣耀 庞文涛 王思童 张莹 He Bing;Zeng Rongyao;Pang Wentao;Wang Sitong;Zhang Ying(School of Physics and Electrical Engineering,Weinan Normal University,Weinan,Shaanxi 714099,China;School of Mathematics and Computer Science,Shaanxi University of Technology,Xi’an 723001,China)
出处 《机电工程技术》 2024年第4期45-49,共5页 Mechanical & Electrical Engineering Technology
基金 国家级大学生创新创业训练计划项目(22XK013)。
关键词 自适应 即时定位与地图构建 多地形机器人 激光雷达 PID adaptive simultaneous localization and mapping(SLAM) multi-terrain robot lidar PID
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