Teaching a robot to draw: hand gesture demonstration based on human-robot interaction

Limei Yang; Zhihao Li; Qujiang Lei; Jie Xu; Yunfu Deng; Yuxin Zhong

doi:10.1117/12.2559707

31 January 2020 Teaching a robot to draw: hand gesture demonstration based on human-robot interaction

Limei Yang, Zhihao Li, Qujiang Lei, Jie Xu, Yunfu Deng, Yuxin Zhong

Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114330M (2020) https://doi.org/10.1117/12.2559707
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands

Abstract

With the development of collaborative robots, robot programming by demonstration (PBD) plays an important role in human-robot interaction, it aims to transfer new skills from observations of tasks demonstrated by humans to robots. In this paper, we proposed a new approach to teach a robot to draw pictures based on human fingertip recognition and hand motion tracking. Combining the robot operating system (ROS), OpenCV and Moveit (motion planning libraries), we capture the finger movement trajectory by using Kinect2 depth camera. Then the trajectory waypoint is sent to the ur5 robotic arm through topic communication to complete the trajectory tracking task. The experiment indicates that the proposed approach allows inexperienced users to efficiently teach a robot to track the demonstrated trajectory.

Citation Download Citation

Limei Yang, Zhihao Li, Qujiang Lei, Jie Xu, Yunfu Deng, and Yuxin Zhong "Teaching a robot to draw: hand gesture demonstration based on human-robot interaction", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114330M (31 January 2020); https://doi.org/10.1117/12.2559707

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KEYWORDS

Cameras

Imaging systems

Skin

Computer programming

Computing systems

Control systems

RGB color model

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