Yuxiu Wu
Papers
2
Total Citations
11
H-Index
2
About
Yuxiu Wu is a researcher specializing in robotics perception, multi-robot coordination, and sensor fusion. Her work addresses critical challenges in autonomous navigation and collaborative robotics, particularly in environments where traditional sensing methods fall short. In her highly cited 2021 paper, "Application of fusion 2D lidar and binocular vision in robot locating obstacles" (8 citations), Wu proposed a novel algorithm that integrates 2D lidar data with binocular vision to overcome limitations such as missing or inaccurate obstacle information. This fusion approach enables robots to obtain precise 3D obstacle data, significantly enhancing their ability to navigate complex, unstructured environments. Earlier, in her 2009 work "Multi-robot Dynamic Pursuit Scheme Based on Behavior-Merging and Task Decision-Making Technology" (3 citations), Wu tackled the challenge of multi-robot cooperation in unknown and dynamic settings. By merging behaviors and optimizing task decision-making, she developed a pursuit scheme that operates effectively without restrictive environmental assumptions. Wu’s contributions have advanced the fields of robotic perception and multi-agent systems, providing practical solutions for real-world applications like search-and-rescue and autonomous exploration. Her work continues to influence researchers developing robust, sensor-integrated robotic systems.
Research Focus
Key Achievements
Top Papers
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