Xiaotong Sun

Hubei University of Technology, Southwest Jiaotong University, Guangdong University of Technology

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About

Xiaotong Sun’s research bridges the frontiers of rehabilitation robotics, aerial manipulation, and autonomous traffic systems, demonstrating a rare versatility across mechanical and control engineering. Sun’s most cited work, “Iterative learning control applied to a hybrid rehabilitation exoskeleton system powered by PAM and FES” (2017, 27 citations), introduces a novel control strategy combining pneumatic artificial muscles and functional electrical stimulation to enhance recovery for patients with motor impairments—a contribution that has informed subsequent adaptive exoskeleton designs. In aerial robotics, Sun’s 2019 paper on a novel omnidirectional aerial robot, driven by four 2-DOF tilting modules arranged in a regular tetrahedron, achieves unprecedented maneuverability by ensuring at least three rotors remain horizontal at any orientation, enabling stable flight in constrained environments. More recently, Sun’s 2025 work on fully autonomous traffic explores the stochastic nature of car-following behavior, revealing critical mobility–safety trade-offs that challenge deterministic models. This research has already garnered early citations for its implications in risk-aware autonomous driving. Sun’s ability to integrate iterative learning, novel mechanical design, and probabilistic modeling marks a distinctive trajectory in robotics and intelligent systems.