双激光雷达温室运输机器人导航系统研制

为解决机器人在温室环境下的自主导航问题,该研究研制了基于双激光雷达的温室运输机器人导航系统,实现温室环境下的地图构建、路径规划和定位导航。融合激光雷达与编码器信息,使用cartographer算法及时定位与地图构建。根据地图与检测点信息,采用Dijkstra算法规划全局路径,使用动态窗口算法规划局部路径,完成自主导航。试验表明,车载系统分别以0.2、0.5和0.8 m/s速度运行时,实际导航路径与目标路径的横向平均偏差小于13 cm,标准差小于5 cm;导航目标点处横向偏差、纵向偏差的平均值不超过9 cm,均方根误差不超过11.2 cm,标准差小于5 cm,航向偏差的平均值小于10°,均方根误差小于12°,标准差小于6°,满足机器人温室运输作业的导航精度需求。

Development of dual-lidar navigation system for greenhouse transportation robot

Abstract: In order to solve the problem of autonomous navigation of robots in greenhouse environment, a navigation system for greenhouse transportation robot based on dual-lidar was developed in this paper, The navigation system consisted of front and rear lidar, compared with the single lidar, the front and rear double lidar could increase the scanning range, reduce the blind area of tracing, improve the efficiency and accuracy of surveying and mapping, and improve the real-time obstacle avoidance ability of the robot. The navigation system of greenhouse transportation robot was composed of a remote monitoring platform and an on-board system. The remote monitoring platform was responsible for selecting the working mode of the on-board system, issuing the the instruction of target points and displaying the location information of the on-board system. As the executor of the instructions, the on-board system was responsible for receiving and executing task instructions ordered by the monitoring platform. Through the real-time communication through wireless network, the remote monitoring platform and the on-board system jointly complete the autonomous navigation task of greenhouse transportation robot. The on-board system hardware mainly consisted of a driving module, a control module, an environmental information perception module, a communication module and a power supply module. The on-board systems software was divided into three layers, user interaction layer, information processing layer and execution layer. The user interaction layer was an open-source Ubuntu-based navigation task scheduler that responsible for adjusting the working mode of the on-board system and issuing target points instructions. The information processing layer was the real-time positioning and map building and fixed-point navigation program based on the Robot Operating System(ROS), which was responsible for collecting the motion information of on-board system and environmental information from lidar, and conducting information fusion. According to the control command and on-board system position and attitude information, map construction, path planning and autonomous navigation were carried out. The executive layer was the mobile platform control program based on the open source real-time operating system of Ubuntu. By collecting the speed information of the encoder, the classical PID algorithm was used to adjust and output the desired Pulse Width Modulation(PWM) wave to control the motor speed, so as to realize the stable and safe movement of the on-board system. The dynamic window algorithm was used to plan the local optimal path to reduce walking time and energy consumption. The test results showed that when the on-board system ran at the speed of 0.2, 0.5 and 0.8 m/s , the average deviation and the standard deviation between the actual navigation path and the target path was less than 13 and 5 cm, respectively; the average value, the root mean square error, the standard deviation of the lateral deviation and longitudinal deviation at each target point was less than 9, 11 and 5 cm, respectively; the average value, the root mean square error, and the standard deviation of the course deviation was less than 10°, 12° and 6°, respectively, which met the navigation accuracy requirements of robot transportation in greenhouse.