【摘要】 针对当下球类陪练机器人人机交互能力不足的问题,提出一种基于树莓派和YOLOv5目标检测算法的新型人机交互模式,使机器人实现前进、后退、左移、右移、抛球、踢球6种不同的动作;通过对在3种不同环境(室内、室外晴天、室外阴天)下搜集的人体姿态数据集进行标定、训练后,得到6种姿态在3种环境中测试集上的识别准确率分别为:室内96.33%、室外晴天95%、室外阴天94.3%。相比基于特征匹配和其他利用手势等小目标检测的算法,基于该算法的机器人具有更高的检测速度和准确性,使机器人更加智能化。更多还原

【Abstract】 In order to solve the problem of insufficient human-computer interaction ability of ball training partner robots,a new human-computer interaction mode based on Raspberry Pi and YOLOv5 algorithm was proposed,which enabled the robot to realize six different actions:forward,backward,left,right,throwing the ball,and kicking the ball.After calibrating and training the data sets collected in three different environments(indoor,outdoor sunny day and outdoor cloudy day),the recognition accuracy of the six poses in the test set under three different environments is 96.33% indoor,95 % outdoor sunny day,and 94.3% outdoor cloudy day,respectively.Compared with other algorithms based on feature matching and small target detection using gestures,the robot has higher detection speed and accuracy,which makes the robot more intelligent.更多还原