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About

Xin Lang is a pioneering roboticist whose research bridges bio-inspired design, soft robotics, and adaptive control. His most impactful work centers on developing soft climbing robots that mimic biological locomotion—most notably, his 2020 paper on a soft rod-climbing robot inspired by snake winding, which has garnered over 200 citations. This work addresses the longstanding challenge of enabling soft robots to climb outer surfaces of rods and tubes with agility and efficiency, opening new possibilities for inspection in constrained environments like pipelines and high-voltage cables. Lang further expanded this paradigm with a quadruped soft robot for climbing parallel rods, demonstrating versatile locomotion through coordinated bending and telescopic actuators. His contributions extend to self-adaptive grasping, where he introduced a bionic torus actuator inspired by sea anemones, capable of enveloping objects of unknown shape and size. In recent years, Lang has advanced robot intelligence through reinforcement learning and Koopman-based robust control, as seen in his 2024 work on rapid online adaptive control for legged robots. His programmable design framework for soft actuators enables complex motions like bending, twisting, and winding within a single actuator class, cementing his reputation as a leader in both soft hardware and intelligent control.