Guoqi Peng

About

Guoqi Peng is a researcher at the forefront of autonomous navigation and robotics, with a primary focus on enabling reliable self-driving in complex, unstructured environments. His most cited work, "Fully Automatic Large-Scale Point Cloud Mapping for Low-Speed Self-Driving Vehicles in Unstructured Environments" (2021, 12 citations), introduces a robust, fully automatic mapping system that fuses data from LiDAR, IMU, RTK-GPS, and wheel encoders. This contribution is critical for low-speed autonomous vehicles and robots operating in off-road or GPS-denied settings, where traditional mapping methods often fail. By achieving seamless multi-sensor fusion and large-scale point cloud generation without manual intervention, Peng’s work directly addresses a key bottleneck in field robotics. His research has practical implications for agriculture, mining, and last-mile delivery, where vehicles must navigate unpredictable terrain. With a growing citation impact, Peng is establishing himself as a rising authority in autonomous mapping and sensor fusion.

Research Focus

Key Achievements

Top Papers

1. 1
   Fully Automatic Large-Scale Point Cloud Mapping for Low-Speed Self-Driving Vehicles in Unstructured Environments

   12 citations · 2021

Key Collaborators

Contact & Links