Development of a Teleoperation System Using Motion Capture Methodologies for Baxter Robot

Abstract

This paper presents the development and implementation of a teleoperation system using motion capture methodologies for the Baxter robot. The system utilizes a Microsoft Kinect V2 camera to capture human motion data and translates it into robot joint angles in real time, enabling intuitive control of the robot's movements. A function approximation technique (FAT) based controller was implemented to enhance the system's stability and performance while compensating for unknown dynamics. The mathematical framework incorporates the Denavit-Hartenberg model for mapping human arm movements to the robot's 7-DOF structure, along with space vector calculations for joint angle determination. Experimental results demonstrate successful real-time motion replication across multiple joint configurations, with the robot effectively mimicking human arm movements. Data analysis of joint positions, velocities, and accelerations confirms the system's capability to maintain accuracy while managing inherent challenges such as network latency and motion jittering. The developed system proves efficient and cost-effective, utilizing readily available hardware components while achieving reliable performance. This work contributes to advancing human-robot interaction in applications where direct human presence may be hazardous or impractical, offering potential benefits across industries including manufacturing, healthcare, and hazardous environment operations.