Haoxin Liu

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About

Haoxin Liu is a robotics researcher specializing in autonomous navigation and path planning for mobile robots, with a particular focus on indoor cleaning robots. His major contributions lie in enhancing the A-star (A*) algorithm to improve both global path optimization and real-time obstacle avoidance. Liu’s most-cited work, "ASL-DWA" (2022, 73 citations), introduces a novel fusion of the A* algorithm with the Dynamic Window Approach (DWA), significantly reducing search nodes and enabling robots to avoid unknown local obstacles while generating smoother, more efficient paths. He further advanced this line of research with "Improved A*-DWA fusion path planning algorithm with ideal path area constraints" (2023), which incorporates area constraints to achieve superior global optimality. Liu also developed RM-Line (2022), a ray-model-based method for extracting straight lines from grid maps, enhancing environmental perception for mobile robots. His work directly addresses the practical challenges of deploying autonomous robots in complex indoor environments, bridging the gap between theoretical path planning and real-world navigation. With a growing citation impact, Liu’s research is foundational for engineers and researchers developing next-generation service robots.