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About

Dongyi Ren is a leading researcher in the field of legged robotics, with a primary focus on the gait control and dynamic locomotion of hydraulic quadruped robots. His work addresses the core challenge of enabling stable, adaptive movement in complex terrains—critical for applications in field investigation, seismic search, and planetary exploration. Ren’s major contributions include pioneering gait planning and control strategies that enhance obstacle-surmounting ability and ensure smooth trunk motion, as demonstrated in his highly cited 2018 paper on recent advances in gait control (18 citations) and his 2019 study on complex dynamic locomotive control (12 citations). More recently, he has advanced the field with optimal trajectory planning and model-predictive control methods, tackling the multi-coupling, multi-variable nature of hydraulic systems. His 2023 and 2025 works on decomposed optimal trajectory control represent a significant step toward real-time, adaptive robot behavior. With a growing citation impact and a clear trajectory of innovation, Ren is shaping the future of robust, high-performance quadruped robots for demanding real-world environments.