智能化农业装备学报（中英文）2026，Vol.7Issue(3)：49-60,12.DOI:10.12398/j.issn.2096-7217.2026.03.005
畜禽舍移动机器人自主导航关键技术试验研究
Experimental study on key technologies of autonomous navigation for mobile robots in livestock and poultry houses
摘要
Abstract
Large-scale and intensive livestock production in China has greatly raised breeding density,elevating pathogen transmission risks and imposing stricter requirements on environmental monitoring and manure handling.Traditional manual methods suffer from low efficiency,and the unstructured barn environment,such as narrow walkways,randomly scattered obstacles,slippery and dusty ground,severely degrades navigation accuracy and robustness of mobile robots.To address these issues,this study proposes a global-local integrated path planning method combining an enhanced Jump Point Search(JPS)algorithm with the Dynamic Window Approach(DWA).For global planning,a multi-dimensional comprehensive cost function,an adaptive jump point optimization strategy,Bezier curve interpolation,and the Douglas-Peucker algorithm for redundant point elimination are introduced to comprehensively optimize global path smoothness,significantly reducing redundant path nodes and sharp turns.For local planning,the weighting parameters of the DWA objective function and kinematic constraints are specifically optimized to enhance the robot real-time dynamic obstacle avoidance and trajectory tracking capabilities.Simulation results on 40×40 and 60×60 standard grid maps show that,compared to the traditional algorithm,the improved JPS algorithm reduces the number of path nodes by 77.55%and 87.14%,cumulative turning angles by 70.91%and 77.97%,and search time by 48.94%and 75.15%,respectively,while consistently maintaining the shortest path length.Physical experiments demonstrate that the integrated JPS-DWA algorithm successfully avoids unknown obstacles.The average lateral,longitudinal,and heading deviations for repeated navigation to three target points are 0.48 cm,-0.66 cm,and-0.17°,respectively,outperforming existing methods and indicating high positioning stability and navigation repeatability.The proposed algorithm achieves accurate and robust autonomous navigation inside complex and unstructured livestock houses,effectively overcoming the limitations of traditional navigation technologies.It provides core technical support for automated mobile robot tasks in livestock houses,such as inspection,disinfection,and cleaning,thereby facilitating the intelligent and efficient transformation of livestock and poultry farming.关键词
移动机器人/自主导航/路径规划/跳跃点搜索算法/动态窗口法Key words
mobile robot/autonomous navigation/path planning/JPS algorithm/DWA algorithm分类
农业科技引用本文复制引用
焦星惠,刘恩光,王锡泉,王帅智,史书阳,丁攀..畜禽舍移动机器人自主导航关键技术试验研究[J].智能化农业装备学报（中英文）,2026,7(3):49-60,12.基金项目
河南省重点研发专项(251111110400) （251111110400）
河南省高等学校重点科研项目计划(25B460006) Key Research and Development Program of Henan Province(251111110400) （25B460006）
Key Scientific Research Project Plan for Higher Education Institutions in Henan Province(25B460006) （25B460006）
