Weiren Shi

Papers

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About

Weiren Shi is a leading researcher in mobile robotics, with a primary focus on intelligent navigation, obstacle avoidance, and sensor fusion. His most influential work, “Path planning of mobile robot based on improved artificial potential field” (2010), with 46 citations, tackles the critical “Goals Nonreachable with Obstacle Nearby” (GNON) problem. By introducing an enhanced potential function that guarantees the goal remains the global minimum, Shi’s method allows robots to navigate freely and reliably toward their targets even in cluttered environments—a fundamental advance in autonomous path planning. In his earlier work, “A Fuzzy-Neural Network Approach To Multisensor Integration For Obstacle Avoidance Of A Mobile Robot” (2009), Shi pioneered a hybrid model combining fuzzy logic and neural networks to fuse data from multiple sensors. This approach enables robots to make robust, real-time decisions for obstacle avoidance, demonstrating his expertise in bridging computational intelligence and practical robotics. Through these contributions, Shi has significantly improved the safety and efficiency of mobile robot navigation, making his research essential reading for students and engineers working on autonomous systems.