Sheng Jin

Papers

Total Citations

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About

Sheng Jin’s research focuses on intelligent control systems for mobile robotics, with a particular emphasis on fuzzy logic-based navigation and obstacle avoidance. His major contributions lie in developing simple yet effective fuzzy logic controllers that enable mobile robots to navigate unknown environments autonomously. His most cited work, "Fuzzy Logic System Based Obstacle Avoidance for a Mobile Robot" (2011), has garnered 22 citations and demonstrates a novel approach to real-time obstacle detection and avoidance using ultrasonic sensors. Building on this, his 2012 paper introduces a single-input fuzzy logic controller (SFLC) that simplifies the control architecture while maintaining robust performance—a design that reduces computational complexity without sacrificing accuracy. This work, cited 10 times, employs singleton fuzzification, simplified Mamdani inference, and centroid defuzzification to control wheel velocities based on obstacle proximity. Jin’s research is notable for its practical, hardware-implementable solutions that bridge the gap between theoretical fuzzy logic and real-world robotic applications. His achievements highlight a commitment to creating accessible, efficient control systems that advance the field of autonomous mobile robotics.