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About

Liu’s research focuses on mobile robotics, path planning, and multi-robot coordination, with key contributions in formation control and obstacle avoidance. His most influential work, “Dynamic Path Planning for Mobile Robot Based on Improved Genetic Algorithm” (28 citations), advances adaptive navigation in dynamic environments. In “Formation Control of Mobile Robots with Active Obstacle Avoidance” (11 citations), he pioneered a unified control algorithm that enables follower robots to avoid obstacles while maintaining relative positioning to a leader, using only relative motion states—eliminating the need for absolute leader data. This work, validated through experiments with nonholonomic robots and vision systems, addresses a critical gap in leader-follower formation literature. Liu also developed rescue robots for disaster relief (4 citations) and proposed a single-mobile-node navigation method for multi-robot systems (2 citations). His vision-based formation control (2 citations) further demonstrates his commitment to reducing reliance on global sensing. With a career spanning over a decade, Liu’s research has practical implications for autonomous exploration, disaster response, and industrial automation, establishing him as a contributor to intelligent robotic systems.