Tsang-Wei Lee

Papers

Total Citations

H-Index

About

Tsang-Wei Lee is a leading researcher in robotics and artificial intelligence, specializing in agile robotic locomotion and bio-inspired control systems. His most influential work, "Learning Agile Robotic Locomotion Skills by Imitating Animals" (2020), has garnered over 75 citations, establishing him as a key figure in bridging the gap between animal dexterity and robotic performance. Lee’s major contribution lies in developing learning-based frameworks that enable robots to replicate the diverse, agile movements of animals—such as running, jumping, and turning—without relying on labor-intensive, manually-designed controllers. By leveraging imitation learning and reinforcement learning, his approach significantly reduces development time while enhancing robotic adaptability in complex environments. This work has profound implications for search-and-rescue missions, exploration, and autonomous systems requiring dynamic mobility. Lee’s research not only advances the field of robotics but also inspires new methodologies in embodied AI. His achievements underscore a commitment to creating more versatile, efficient machines, making him a pivotal figure for students and researchers interested in the future of autonomous locomotion and animal-inspired engineering.