Bo-Han Shih
Papers
2
Total Citations
43
H-Index
2
About
Bo-Han Shih is a robotics researcher whose work centers on human-robot interaction, motion imitation, and adaptive control for humanoid and dual-arm robotic systems. His most influential contribution is the development of a real-time human motion imitation framework for anthropomorphic dual-arm robots, detailed in his highly cited 2013 paper (34 citations). By leveraging a Kinect sensor to capture human skeleton joint positions and employing Cartesian impedance control, Shih enabled robots to intuitively follow human demonstrations, advancing intuitive programming and teleoperation. He further extended this work with a 2013 study on Cartesian position and force control, integrating adaptive impedance and compliance capabilities for humanoid robot arms. This research introduced End-Effector Fixation Control (EEFC) to enhance precision in reaching target points, demonstrating robust performance in tasks requiring both position and force regulation. Shih’s contributions have been instrumental in bridging human motion and robotic actuation, with his citation record reflecting the practical value of his control strategies for applications in assistive robotics, manufacturing, and human-robot collaboration.
Research Focus
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Top Papers
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