高金潇 陈亦楠

摘  要：人工智能技术的兴起也推进了人机交互的快速发展。该系统利用Kinect视觉图像传感器识别人体骨骼数据，并完成对操作者动作的识别。通过以计算机软件为核心的上位机平台对实时数据的滤波处理、编写算法，实现从数据到控制信号的转换。系统通过串口通信的传输方式将信号传送至以Arduino为核心的下位机平台，进而完成对舵机的控制。为验证理论的可行性，团队搭建了4自由度的机械臂控制系统，并完成软件开发，可实时在计算机操作界面上显示当前骨骼角度及动作状态等其他功能。实验数据表明，基于Kinect的动作识别方法能够有效地完成预期动作的跟踪，并完成规定物体的抓取和移送，具有极高的可操作性。

关键词：Kinect  Arduino  骨骼角度  动作跟踪  机械臂平台

中图分类号：TP241   文献标识码：A 文章编号：1672-3791（2019）05（c）-0001-05

Abstract： The rise of artificial intelligence technology has also promoted the rapid development of human-computer interaction. The system uses the Kinect visual image sensor to identify human bone data and complete the recognition of the operator's movements. Through the filtering process of real-time data by the host computer platform with computer software as the core， the algorithm is programmed to realize the conversion from data to control signals. The system transmits the signal to the lower computer platform with Arduino as the core through the transmission mode of the serial communication， thereby completing the control of the steering gear. In order to verify the feasibility of the theory， the team built a 4-DOF robotic arm control system and completed software development. It can display other functions such as the current bone angle and motion status in real time on the computer operation interface. The experimental data shows that the Kinect-based motion recognition method can effectively complete the tracking of the expected motion and complete the grasping and transfer of the specified objects， which has extremely high operability.

Key Words： Kinect; Arduino; Bone angle; Motion tracking; Robotic arm platform

隨着近些年来人工智能领域的大力发展，人机交互成为了人们关注的热点问题。动作识别在人们日常医疗、教育、娱乐等诸多领域有着广泛的应用。此外，动作分析作为工业工程的关键技术之一，实现该技术的相关方法却一直停留在手工阶段，这不仅工作量大，而且效率低。人体姿势及特定动作是一种人与周围信息或生物进行信息交互的方式。围绕动作识别的研究在国际上可以追溯到20世纪80年代，此后，人体动作识别的研究逐渐渗入到各个领域的研究开发，并得到迅速的发展。

无线设备大大促进了人机交互的发展，但目前其一定程度上依赖人工连续操作，十分不便。……