Changyong Li
Papers
2
Total Citations
13
H-Index
2
About
Changyong Li is a rising researcher at the forefront of intelligent robotics and autonomous perception, whose work is driving practical advancements in both industrial automation and autonomous driving. His primary research areas encompass multi-robot path planning, 3D object detection, and multimodal sensor fusion. Li’s most impactful contribution, a 2025 paper integrating an improved A* algorithm with the Dynamic Window Approach for multi-robot path planning, has already garnered 11 citations. This work directly addresses the growing need for efficient automation in settings like chemical laboratories, where robots must navigate complex environments to transport materials. In a second notable 2025 paper, Li introduces PPF-Net, a novel Pillar-Point Fusion network for multimodal 3D object detection. By elegantly fusing sparse LiDAR point clouds with rich semantic data from camera images, PPF-Net achieves robust detection performance with a simpler architecture, offering a compelling solution for robotics and autonomous vehicles. Through these contributions, Li is establishing himself as an innovator in creating more intelligent, perceptive, and collaborative robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2