基于信息融合的智能推料机器人设计与试验

Design and Experiment of Intelligent Feed⁃pushing Robot Based on Information Fusion

饲料的定期推送是奶牛饲喂过程中的重要环节,针对现有推料机器人功能单一,无法满足奶牛饲喂需求的问题,开发了奶牛智能推料机器人。构建奶牛、饲料和牛栏参照物识别与分割的YOLACT模型,融合掩膜图像、深度图与ORB-SLAM3定位信息,实现觅食奶牛的快速定位与机器人导航信息的提取;基于信息融合提出智能推料算法,根据觅食奶牛的定位信息、投料时间信息、机器人的导航信息,自动选择工作模式,控制机器人沿着预定的轨迹,实现推料、集料送料、清料等多模式推料功能,满足奶牛个性化自由采食需求,提升饲料利用率。试验结果表明:觅食奶牛的位置识别定位精度为±0.1 m,奶牛识别率为100%,机器人导航精度为±0.8 cm,智能推料准确率为100%,算法运行速率为12 f/s,满足复杂环境下机器人智能推料的要求。

The regular pushing of feed is an essential part of feeding process of dairy cows.Aiming at the problem that the existing feed⁃pushing robots have single function,which cannot collect and transport the feed according to the cows'position to meet their needs,an intelligent feed⁃pushing robot for dairy cows was developed.Firstly,YOLACT instance segmentation model was used to identify cows,feed,and square rod and obtain the mask.Secondly,dynamic objects were removed at ORB SLAM3 by using the mask to improve the positioning accuracy,and then the real⁃time robot position was obtained.Thirdly,the location of foraging cows was calculated by combining the mask,stereo camera depth image and the robot position,and the distance between the robot and the cattle barn was calculated by using mask and depth image with the square rod as reference.Finally,during the working process of the robot,the distance between the robot and the cattle barn was kept unchanged,and the independent decisions were made by the robot according to the foraging cows position and the feeding time,so as to realize the multi⁃mode feeding functions of push,collect⁃transport and clean,so it can improve the feed utilization efficiency and meet the free feeding needs of cows.The research and experimental results showed that on the TUM RGB D dataset,compared with ORB SLAM3,the proposed algorithm can effectively reduce the positioning error in dynamic environments;the foraging cows position calculation accuracy was±0.1 m,and each cow can be recognized;the distance calculation accuracy between the robot and the cattle barn was±0.8 cm;the working mode selection accuracy was 100%;and the algorithm running rate was 12 f/s.The robot met the requirements of intelligent feeding of robots in complex environments.