Papers
4
Total Citations
31
H-Index
4
About
Wang Wang is a robotics and agricultural automation researcher whose work focuses on the development of intelligent navigation systems for autonomous agricultural robots, particularly in orchard environments. Their research sits at the intersection of mobile robotics, sensor fusion, and precision agriculture, addressing practical challenges that limit the scalability of automated farming operations. Among Wang's most significant contributions is the development of integrated navigation frameworks that combine LiDAR, IMU, and GNSS technologies to enhance localization reliability and obstacle avoidance in complex orchard terrain. Their work on cooperative navigation systems for spraying-dosing robot groups represents a particularly innovative step forward, introducing collaborative multi-robot architectures that ensure uninterrupted field coverage even when individual units require resupply. Wang has also applied deep reinforcement learning — specifically Double-DQN algorithms — to path-tracking control, improving both accuracy and driving stability in tractor-trailer systems. With a publication record spanning from early embedded systems design in 2019 through cutting-edge sensor fusion research in 2024, Wang's trajectory reflects steady growth in technical sophistication. Their most-cited works have collectively garnered approximately 31 citations, demonstrating meaningful influence on autonomous agricultural robotics — a field increasingly critical to sustainable food production and farm labor efficiency.
Research Focus
Key Achievements
Top Papers
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- 4Design of Control System for ARM Vehicle Robot4 citations · 2019