Xianglong Dai
Papers
1
Total Citations
4
H-Index
1
About
Xianglong Dai is a robotics researcher whose work centers on autonomous navigation and perception in agricultural environments. His primary contributions lie in developing practical sensing and obstacle detection systems for field robots, with a particular focus on vineyard applications. In his most-cited work, "Obstacle detection system for autonomous vineyard robots based on passthrough filter" (2018, 4 citations), Dai tackles the critical challenge of enabling safe autonomous operation in complex, unstructured agricultural settings. The research addresses the difficulty of using onboard 3D LiDAR to detect obstacles and plan paths in real-time, proposing a passthrough filtering approach to create and update environmental representations. This work is notable for its direct application to precision agriculture, where reliable obstacle avoidance is essential for deploying robots in uneven terrain with irregular vegetation. While his citation count is modest, Dai's research contributes to the growing field of agricultural robotics, helping bridge the gap between laboratory algorithms and real-world deployment in vineyards and other challenging outdoor environments.
Research Focus
Key Achievements
Top Papers
- 1