基于运动学的医疗服务机器人人体跟踪系统控制

Yanran Long, Yulin Xu, Zixuan Xiao, Zheping Shen
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引用次数: 1

摘要

为了实现医疗服务机器人的人体跟随,利用Kinect v2对目标人进行实时检测,并采用改进的高斯滤波算法对深度图像进行降噪。本文采用卡尔曼滤波算法对人体运动信息进行预测,从而保证更安全、更可靠的实时跟踪。当目标字符被阻挡时,可以安全有效地停止机器人。该系统利用目标人的手势来启动或停止跟踪,可以实现良好的人机交互。最后,设计了一系列人体跟随测试实验,验证了所提方法的有效性以及机器人系统在医院环境下实现人体跟随的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Kinect-based Human Body Tracking System Control of Medical Care Service Robot
In order to realize the human body following of medical care service robot, Kinect v2 is used to detect the target person in real time, and the improved Gaussian filter algorithm is used to denoise the depth image. In this paper, Kalman filtering algorithm is used to predict human movement information, thus ensuring safer and more reliable real-time tracking. When the target character is blocked, the robot can be stopped safely and effectively. This system uses the gesture of the target person to start or stop following, and it can realize good human-computer interaction. Finally, a series of human body following test experiments are designed to verify the effectiveness of the proposed method and the feasibility of the robot system to achieve human body following in hospital environment.
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