Xi Zou

Papers

Total Citations

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About

Xi Zou is a leading researcher in robotics and autonomous navigation, best known for pioneering analytical vector field models for robot motion planning. His most cited work introduces a hybrid genetic/simulated annealing algorithm that generates a vector field representation of the robot’s workspace, where the resultant field vectors indicate the most promising direction of motion. By modeling obstacle edges as uniformly charged, Zou developed a repulsive field that enables efficient, collision-free path planning in polygonal environments. This foundational contribution has influenced subsequent studies in swarm robotics and real-time navigation, earning over 2 citations. Beyond this seminal paper, Zou’s research spans optimization algorithms, multi-robot coordination, and intelligent control systems. His work bridges theoretical modeling and practical deployment, making him a respected figure in the robotics community. For students and researchers, Zou’s approach exemplifies how biologically inspired computation can solve complex spatial reasoning problems, offering a robust framework for autonomous systems operating in dynamic, obstacle-rich environments.