基于Kinect的六轴工业机器人异常姿态检测方法

工业机器人异常姿态检测是保障工业机器人安全作业的重要手段。针对已有方法存在检测准确率低和时效性不足的问题，提出了一种基于Kinect相机的六轴工业机器人异常姿态检测方法。该方法使用Kinect相机采集工业机器人彩色图像和深度图像，通过YOLOF目标检测算法得到彩色图像中工业机器人关节轴的信息，结合深度图像转换为对应三维坐标，参考工业机器人结构特性，构造机器人关节向量，提取角度特征，进行工业机器人姿态特征表示，基于欧式距离和余弦相似度进行姿态匹配，检测工业机器人异常姿态。本文的方法结合了工业机器人关节轴三维信息可对姿态进行更加精确的匹配。构建了六轴工业机器人作业视频数据集并进行了异常姿态检测。实验结果表明，本文的工业机器人异常姿态检测方法准确率为96.6%,单帧图像检测时间为43 ms,满足机器人安全监控实际应用需求。

Abnormal posture detection method of six-axis industrial robot based on Kinect

The abnormal posture detection of industrial robots is an important means to ensure the safe operation of industrial robots. Aiming at the problems of low detection accuracy and insufficient timeliness of existing methods, a method for abnormal posture detection of six-axis industrial robots based on Kinect camera was proposed. The method uses the Kinect camera to collect the color image and depth image of the industrial robot, obtains the information of the joint axis of the industrial robot in the color image through the YOLOF target detection algorithm, converts the depth image into the corresponding three-dimensional coordinates, refers to the structural characteristics of the industrial robot, and constructs the robot joint vector. The angle feature is extracted, the attitude feature representation of the industrial robot is performed, and the attitude matching is performed based on the Euclidean distance and the cosine similarity to detect the abnormal attitude of the industrial robot. The method in this paper combines the three-dimensional information of the joint axis of the industrial robot to match the pose more accurately. A six-axis industrial robot working video dataset is constructed and abnormal posture detection is carried out. The experimental results show that the accuracy of the abnormal posture detection method of industrial robots in this paper is 96.6%, and the detection time of a single frame image is 43 ms, which meets the practical application requirements of robot safety monitoring.