羊舍自主巡检机器人设计与试验

doi:10.13733/j.jcam.issn.2095-5553.2025.01.012

摘要/Abstract

摘要： 针对规模化羊舍人工劳动强度大、作业效率低等问题，设计羊舍自主巡检机器人系统。该系统基于2D激光雷达的即时定位与建图（SLAM）技术，自主导航系统使用基于扩展卡尔曼滤波数据融合的AMCL定位算法实现机器人的定位，采用Gmapping算法构建羊舍环境地图，并采用A*和DWA算法规划机器人巡检路径，最终实现舍内地图构建、系统实时定位、多目标点路径规划以及动态避障。机器人导航精度试验表明，巡检机器人横向偏差均值不超过8.3cm，纵向偏差均值不超过7.1cm；航向偏差的均值不超过6.1°。该系统构建的环境地图精度较高，能够实现对机器人的有效定位，并且能够以实现羊舍的循环巡航和自动躲避周边障碍物，导航精度满足羊舍自主导航需求。

关键词: 羊舍, 巡检机器人, 多传感器融合, 路径规划, 扩展卡尔曼滤波

Abstract: In order to solve the problems of high labor intensity and low working efficiency of largescale sheep house, an autonomous inspection robot system for sheep house is designed. The system is based on the realtime positioning and mapping （SLAM） technology of 2D LiDAR. The autonomous navigation system uses the AMCL positioning algorithm based on extended Kalman filter data fusion to realize the positioning of the robot, uses the Gmapping algorithm to construct the environment map of the sheep shed, and uses the A* and DWA algorithms to plan the inspection path of the robot. Finally, it realizes the construction of the map in the house, real-time positioning of the system, multi-objective point path planning and dynamic obstacle avoidance. The robot navigation accuracy test shows that the average lateral deviation of the patrol robot does not exceed 8.3cm, the average longitudinal deviation does not exceed 7.1cm, and the average heading deviation does not exceed 6.1°. The environmental map constructed by this system has high accuracy, can effectively locate the robot, and can realize the cyclic cruising and cruising of the sheep house.

Key words: sheep house, inspection robot, multi-sensor fusion, path planning, extended kalman filtering

中图分类号:

赵宁磊, 程曼, 袁洪波, 王媛, 蔡振江. 羊舍自主巡检机器人设计与试验[J]. 中国农机化学报, 2025, 46(1): 78-84.

Zhao Ninglei, Cheng Man, Yuan Hongbo, Wang Yuan, Cai Zhenjiang. Design and experiment of autonomous inspection robot for sheep house[J]. Journal of Chinese Agricultural Mechanization, 2025, 46(1): 78-84.

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