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About

Jingyu Xiang is a robotics researcher whose work focuses on autonomous mobile robot navigation, with a particular emphasis on variable-resolution mapping and path planning in unknown environments. His major contribution lies in developing novel roadmap generation methods that integrate both position and velocity information—or, for car-like robots, orientation—into graph-based representations of continuous state spaces. This approach enables more efficient and safer navigation by allowing robots to plan paths while accounting for dynamic constraints and safety considerations. Among his most cited works, a 2012 paper on variable-resolution velocity roadmap generation for mobile robots has garnered 7 citations, highlighting its relevance to the field. Xiang also pioneered methods for simultaneous map building and real-time path planning using omnidirectional distance sensors, as well as obstacle avoidance strategies that combine particle control with potential field methods. His research addresses the critical challenge of operating under statistical uncertainty in observation and locomotion, making his contributions valuable for advancing autonomous systems in complex, real-world environments.