Wenkai Chang

University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shandong Institute of Automation

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About

Wenkai Chang is a robotics researcher whose work bridges the critical gap between ground and aerial systems for infrastructure inspection and emergency response. His primary research areas include power line inspection robotics, active SLAM for visual navigation, and self-modeling control for fire-fighting robots. Chang’s most impactful contribution is the development of a power line inspection robot with hybrid operation modes (2017, 69 citations), which uniquely combines climbing and flying capabilities—allowing it to land on overhead ground wires and fly over obstacles, a significant advancement for autonomous utility maintenance. More recently, his work on active SLAM with dynamic viewpoint optimization (2025) addresses the limitations of fixed-mounted visual sensors, proposing a method to enhance robustness in autonomous navigation. Additionally, his research on self-modeling tracking control for crawler fire-fighting robots (2019) introduces a causal network-based approach to improve motion control in hazardous environments. Chang’s contributions are particularly notable for their practical applications in high-risk scenarios, from power line maintenance to firefighting, demonstrating a commitment to developing robots that can operate reliably in complex, unstructured environments.