Jin‐Siang Shaw
Papers
14
Total Citations
106
H-Index
7
About
Jin-Siang Shaw is a robotics and automation researcher whose work spans intelligent manipulation, computer vision, robot control, and autonomous mobile systems. With a career dedicated to advancing practical robotic solutions, Shaw has made significant contributions to eye-in-hand vision systems, force-controlled grippers, and autonomous guided vehicles (AGVs). His 2016 work on single-camera object identification for robot grippers — employing SURF algorithms within an eye-in-hand architecture — and his companion research on vision-servo Delta robots for conveyor-based pick-and-place tasks together reflect a sustained commitment to bringing intelligent perception into industrial automation contexts. Notably, his 2022 study on artistic robotic pencil sketching introduced closed-loop force sensing to simulate human drawing pressure and compensate for pencil wear, demonstrating creative versatility alongside engineering rigor. Shaw has also explored shape memory alloy actuators with fuzzy sliding-mode control, adaptive backstepping techniques for flexible-joint manipulators, and ROS-based AGV platforms integrating SLAM and RGBD sensing. His accumulated citations — with multiple papers exceeding 9–16 citations — reflect growing recognition in a competitive field. Taken together, Shaw's body of work positions him as a thoughtful contributor to intelligent robotics, bridging control theory, machine vision, and real-world manufacturing applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2Vision servo based Delta robot to pick-and-place moving parts13 citations · 2016
- 3Artistic robotic pencil sketching using closed-loop force control11 citations · 2022
- 4Force control of a robot gripper featuring shape memory alloy actuators9 citations · 2014
- 5Development of an AI-enabled AGV with robot manipulator9 citations · 2019
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