Kinect-Based Motion Recognition Tracking Robotic Arm Platform

Jinxiao Gao, Yinan Chen, Fuhao Li
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引用次数: 5

Abstract

The development of artificial intelligence technology has promoted the rapid improvement of human-computer interaction. This 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.
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基于运动学的运动识别跟踪机械臂平台
人工智能技术的发展促进了人机交互的快速提高。该系统利用Kinect视觉图像传感器识别人体骨骼数据,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进行滤波处理,编写算法实现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输到以Arduino为核心的下位机平台,从而完成对舵机的控制。为了验证理论的可行性,团队搭建了一个四自由度机械臂控制系统,并完成了软件开发。可在计算机操作界面上实时显示当前骨骼角度、运动状态等其他功能。实验数据表明,基于kinect的运动识别方法能够有效地完成对预期运动的跟踪,完成对指定物体的抓取和转移,具有极高的可操作性。
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