Max Robotics — Global Service Robot Directory + US Certification

About

Hsien-Chung Lin is a robotics researcher whose work spans robotic assembly automation, human-robot interaction, safety-critical control, and deformable object manipulation. He is perhaps best known for his foundational contributions to peg-hole-insertion problems, where his methods for autonomous alignment using force/torque sensing (97 citations) and learning from human demonstration (79 citations) have significantly advanced the state of industrial robot programming. By enabling robots to acquire human assembly skills rather than relying on painstaking manual tuning, Lin helped bridge a critical gap between human dexterity and robotic consistency. Beyond assembly, Lin has made notable contributions to robot safety and efficiency. His introductory work on Control Barrier Functions for robotic systems (69 citations) has become a valuable resource for researchers designing safety-aware controllers, while his real-time collision avoidance algorithms and the SERoCS framework address the practical demands of human-robot collaboration in dynamic factory environments. An early and distinctive contribution was his autonomous water vapor plume-tracking robot using passive resistive polymer sensors (76 citations), demonstrating breadth across sensing and autonomous systems. Rounding out his portfolio, Lin has advanced trajectory optimization and deformable object state estimation, reflecting a comprehensive vision for robust, intelligent, and safe robotic systems in next-generation manufacturing.