Papers
12
Total Citations
153
H-Index
6
About
Po Ting Lin is a leading researcher in robotics and automation, whose work bridges the gap between theoretical mechanics and practical industrial applications. His primary research areas include robot kinematics, compliance error compensation, and gravity balancing for serial manipulators, as well as autonomous navigation and soft robotics. Lin’s most impactful contribution is his analytical model for compensating compliance errors in robot end-effectors during milling, accounting for joint stiffness uncertainties—a paper that has garnered 51 citations and addresses a critical challenge in precision manufacturing. He also pioneered the concept of gravity balancing reliability for spring-articulated robots, introducing probabilistic methods to ensure performance under uncertainties (24 citations). In the realm of autonomous systems, Lin developed a probabilistic indoor positioning and navigation method for autonomous ground vehicles using wireless measurements (22 citations), and advanced inline inspection techniques for mass-customization production lines (22 citations). His work extends to soft robotics, where he has modeled soft gripper kinematics using parametrically defined Denavit-Hartenberg tables, and to infrastructure inspection via unmanned aerial systems with metamodeling-based image correction. With a portfolio that spans from fundamental mechanics to cutting-edge automation, Lin’s research is essential reading for engineers and roboticists seeking to enhance robot accuracy, reliability, and autonomy in real-world settings.
Research Focus
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