中国猪业 ›› 2026, Vol. 21 ›› Issue (4): 102-111.doi: 10.16174/j.issn.1673-4645.2026.04.011

• 专题报道 • 上一篇    下一篇

多层楼房养殖场无人消杀装备系统设计研究

陈薪蓉1，庞武林2，孙二超2，钟儒清3，袁培银1*，刘向东2,4*   

  1. 1重庆交通大学，重庆400074； 

    2广西扬翔集团股份有限公司，广西贵港537100； 

    3中国农业科学院北京畜牧兽医研究所，北京100193； 

    4华中农业大学，湖北武汉430070

  • 出版日期:2026-08-25 发布日期:2026-08-25
  • 作者简介:作者简介：陈薪蓉（2003-），女，硕士研究生，主要从事机械设计及自动化研究，E-mail：18258072304@163.com 通信作者：袁培银（1987-），男，博士，教授，主要从事机械设计及自动化研究，E-mail：yuanpy@cqjiu.edu.cn； 刘向东（1983-），男，博士，副教授，研究方向为智慧养猪技术与楼房养猪模式的创新与应用，E-mail：liuxiangdong@mail.hzau.edu.cn

System design of unmanned disinfection equipment for multi-story livestock farms

CHEN Xinrong1, PANG Wulin2, SUN Erchao2, ZHONG Ruqing3, YUAN Peiyin1*, LIU Xiangdong2,4*   

  1. 1Chongqing Jiaotong University, Chongqing 400074, China; 

    2Guangxi Yangxiang Group Co., Ltd., Guigang 537100, China; 

    3Institute of Animal Sciences of CAAS, Beijing 100193, China; 

    4Huazhong Agricultural University, Wuhan 430070, China

  • Online:2026-08-25 Published:2026-08-25

摘要： 针对传统畜牧业人工消杀效率低、盲区大、人员感染风险高等问题，本文设计了一套面向多层楼房复杂养殖环境的无人消杀装备。首先，基于阿克曼转向底盘和多传感器融合技术，构建了具备高通过性与可靠性的硬件平台；其次，针对传统蚁群算法收敛慢、易陷入局部最优解的缺点，提出了一种融合人工势场法和改进型蚁群算法的双层架构，引入TEB算法实现局部动态避障；最后，通过ROS系统搭建了集环境感知、路径规划与精准喷洒于一体的智能控制体系。研究表明，复杂路况下该装备定位误差控制在依3 cm，消杀效率达95%以上，消杀覆盖率达98%以上，灭菌率达到100%，对比传统人工消杀，效率提升40%，药剂用量降低30%。验证了系统在多层楼房养殖场作业有效性与优越性，相关技术可为畜牧业装备智能化发展提供科学支撑。

关键词: 猪场, 无人消杀装备, 路径规划, 蚁群算法, 人工势场法, 多传感器融合

Abstract: To address the problems of low efficiency, large blind spots, and high personnel infection risk in manual disinfection for traditional livestock farming, this paper presented an unmanned disinfection equipment tailored for complex multi-story building breeding environments. First, a hardware platform with high maneuverability and reliability was built based on an Ackermann steering chassis and multi-sensor fusion technology. Second, to overcome the slow convergence andsusceptibility to local optima of conventional ant colony algorithms, a two-layer architecture integrating the artificial potential field method and an improved ant colony algorithm was proposed, and the Timed Elastic Band (TEB) algorithm was introduced to achieve local dynamic obstacle avoidance. Finally, an intelligent control system that integrates environmental perception, path planning, and precise spraying was established using the Robot Operating System (ROS). Experimental results demonstrated that under complex road conditions, the positioning error of the equipment was controlled within ±3 cm, the disinfection efficiency exceeded 95%, the disinfection coverage rate surpassed 98%, and the sterilization rate reached 100% , which verified the effectiveness and superiority of the system for operation in multi-story livestock buildings. The relevant technologies can provide scientific support for the intelligent development of animal husbandry equipment.

Key words: pig farm, unmanned disinfection equipment, path planning, ant colony algorithm, artificial potential field method, multi-sensor fusion

中图分类号:  S828；S851.36

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ISSN 1673-4645
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