Jinyong Shangguan
Papers
6
Total Citations
84
H-Index
4
About
Dr. Jinyong Shangguan is a leading researcher in autonomous mobile robotics, with a primary focus on intelligent navigation, motion planning, and control for wheeled robots operating in complex environments. His work masterfully integrates deep reinforcement learning, optimal trajectory planning, and model predictive control to solve fundamental challenges in robot autonomy. Dr. Shangguan’s most impactful contribution is his 2023 paper on "Navigation of Mobile Robots Based on Deep Reinforcement Learning," which has garnered 47 citations for its novel approach to reward function optimization and knowledge transfer. He has also developed a target-oriented path planning algorithm using an improved A* and dynamic windows approach (14 citations), and pioneered an optimal trajectory planning method for underactuated wheeled inverted pendulum vehicles navigating unknown environments (12 citations). His recent work extends to adaptive obstacle avoidance for multi-robot formations in narrow alleyways and path tracking for car-like robots on slopes. With a growing citation record and a 2025 publication on enhanced calibration for robotic 3D scanning systems, Dr. Shangguan is establishing himself as a versatile innovator pushing the boundaries of autonomous navigation from theory to practical, real-world deployment.
Research Focus
Key Achievements
Top Papers
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- 6Enhanced Calibration Method for Robotic Flexible 3D Scanning System2 citations · 2025