Dexian Wang

Papers

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About

Dexian Wang is a leading researcher in intelligent robotics, specializing in path planning and autonomous navigation for complex, dynamic environments. His work is pivotal in advancing mobile robot applications across logistics, healthcare, service, and critical infrastructure maintenance. Wang’s major contributions include the development of an improved A* algorithm for intelligent mobile robots, which enhances the creation of optimal trajectories in challenging settings—a paper that has garnered 12 citations since 2024. He further innovated with a fusion algorithm combining Jump Point Search (JPS) and Dynamic Window Approach (DWA) for substation inspection robots, addressing the persistent challenges of prolonged execution times and high memory consumption in traditional global path planning methods. This work, with 11 citations, demonstrates his ability to solve real-world operational bottlenecks. Wang’s research is notable for its direct industrial applicability, particularly in automating hazardous inspection tasks. His achievements underscore a commitment to making robots more efficient and reliable in mission-critical roles, establishing him as a key figure in the evolution of intelligent autonomous systems.