Peng Xie
Papers
1
Total Citations
12
H-Index
1
About
Peng Xie is a robotics researcher whose work centers on autonomous navigation and perception for unmanned ground vehicles in complex agricultural environments. His most cited paper, "LiDAR-Based Negative Obstacle Detection for Unmanned Ground Vehicles in Orchards" (2024, 12 citations), tackles a critical safety challenge: detecting ditches and potholes that threaten robot mobility. By proposing a novel LiDAR tilt mounting configuration at 40°, Xie dramatically reduces the sensor blind spot from 3 meters to just 0.21 meters, enabling reliable detection of negative obstacles that standard systems miss. This contribution directly addresses a key gap in off-road robotics, where terrain hazards are often invisible to conventional sensors. Xie’s work exemplifies how sensor placement optimization can yield practical, high-impact solutions for field robotics. His research is particularly valuable for advancing autonomous systems in precision agriculture, where safe navigation through uneven orchard terrain is essential. With growing interest in agricultural automation, Xie’s approach to negative obstacle detection represents a meaningful step toward more robust and reliable unmanned ground vehicles.
Research Focus
Key Achievements
Top Papers
- 1