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About

Junlong Xiao is a robotics researcher whose work spans soft robotics, bioinspired locomotion, and intelligent control systems. He has made significant contributions to the design and engineering of adaptive robotic platforms capable of operating in complex, unstructured environments. His most cited work, "A Variable Structure Pneumatic Soft Robot" (2020, 73 citations), introduced an innovative gripper capable of dynamically adapting its structure across a range of object sizes — a notable advancement in soft robotic manipulation. Complementing this, his multimodal soft robot research (47 citations) addressed a critical limitation in the field by developing bionic omnidirectional actuators that enable robots to perform diverse tasks across challenging terrains. Xiao's research extends beyond soft robotics into quadruped locomotion with three-dimensional flexible legs, shape memory alloy modular systems, and gas–liquid phase transition actuators, reflecting a broad design philosophy centered on adaptability and mechanical intelligence. His work in reinforcement learning-based control, specifically applying deep deterministic policy gradient methods to manipulator systems (12 citations), demonstrates his interdisciplinary reach into adaptive control theory. More recently, his review of lower limb exoskeletons signals a growing interest in human-assistive technologies. Across his portfolio, Xiao's research consistently pushes toward robots that are both structurally versatile and environmentally responsive.