A Joint-Cartesian Hybrid Motion Mapping Method for Real-Time Teleoperation Based on Human Arm Kinematic Characteristics
Teleoperation can help robots perform complex tasks in situations where automation is impractical or where cooperation with humans is needed. In this work, we present a human-robot workspace mapping method for teleoperation based on human arm kinematic characteristics. First, the human-robot joint s...
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Published in | 2023 IEEE International Conference on Real-time Computing and Robotics (RCAR) pp. 298 - 303 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
17.07.2023
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Subjects | |
Online Access | Get full text |
DOI | 10.1109/RCAR58764.2023.10249512 |
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Summary: | Teleoperation can help robots perform complex tasks in situations where automation is impractical or where cooperation with humans is needed. In this work, we present a human-robot workspace mapping method for teleoperation based on human arm kinematic characteristics. First, the human-robot joint space mapping is completed using human arm joint angles, which cover the entire robot workspace. And the human-robot Cartesian space mapping is completed using the human wrist pose, which makes the elaborate manipulation easy. Then, a hybrid space mapping method is designed, which combines the advantages of the above two methods and switches between different mapping methods based on gesture recognition. Finally, the experimental results show that the hybrid mapping method presented can improve intuition and flexibility in teleoperation tasks, and a real-time demonstration of the experiments is provided. |
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DOI: | 10.1109/RCAR58764.2023.10249512 |