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污水管道清淤机器人行走路径自动感知方法研究

Research on Automatic Sensing Method of Walking Path of Sewage Pipeline Dredging Robot
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摘要 该文旨在开发一种用于污水管道清淤机器人行走路径自动感知的方法,以便全面掌握管道清淤机器人的当前作业位置.该方法依据管道清淤机器人的结构和工作原理,利用二维测距激光雷达发射激光脉冲测量当前清淤机器人坐标位置信息.通过将坐标信息进行转换和映射处理,获取清淤机器人作业3D地形位置信息.运用四次曲线计算该3D地形位置信息中的曲率数值,根据不断变化的曲率数值生成清淤机器人行走路径.实验结果表明:该方法坐标转换百分比不受污水管道淤堵覆盖程度影响,坐标转换百分比始终高于95%;感知清淤机器人路径消耗时间少,实时性好;感知清淤机器人转弯角度差值仅为1°,路径感知精度高. In order to more fully grasp the current working position of the pipeline dredging robot,the au-tomatic sensing method of the walking path of the sewage pipeline dredging robot is studied.Based on the structure and working principle of the pipeline dredging robot,this method uses the two-dimensional range-finding lidar to emit laser pulses to measure the current coordinate position information of the dredging robot,and after the coordinate information is transformed and mapped,the task of the dredging robot is obtained 3D terrain location information.The quartic curve method is used to calculate the quartic curve curvature value in the 3D terrain position information of the dredging robot operation,and the walking path of the silting robot is generated according to the continuously changing quartic curve curva-ture value.The experimental results show that the coordinate conversion percentage of this method is not affected by the degree of sewage pipeline blockage coverage,and the coordinate conversion percentage is always higher than 95%;the sensing of the dredging robot path consumes less time and has better real-time performance;the sensing of the dredging robot has a poor turning angle;the value is only 1°,and the accuracy of the walking path of the sensing dredging robot is relatively high.
作者 李新 徐军 LI Xin;XU Jun(Bengbu College of Technology and Business,Bengbu 233000,China)
机构地区 蚌埠工商学院
出处 《通化师范学院学报》 2024年第8期1-8,共8页 Journal of Tonghua Normal University
基金 蚌埠工商学院2023年校级教研项目(2023XJjyxm003) 蚌埠工商学院2022年校级教研项目(2022XJjyxm037)。
关键词 污水管道 清淤机器人 行走路径 自动感知 地形重建 路径生成 sewage pipeline dredging robot walking path automatic perception terrain reconstruction path generation
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