Xiangyang Peng
Papers
1
Total Citations
23
H-Index
1
About
Xiangyang Peng is a leading researcher in intelligent robotics and visual perception systems, with a particular focus on autonomous inspection technologies for power infrastructure. His most cited work, "Overhead ground wire detection by fusion global and local features and supervised learning method for a cable inspection robot" (2018, 23 citations), addresses a critical challenge in robotic obstacle crossing: reliably detecting overhead ground wires under varying illumination and open surroundings. Peng’s major contribution lies in developing an adaptive homography-based approach that fuses global and local visual features with supervised learning, enabling cable inspection robots to autonomously and accurately grasp lines during obstacle negotiation. This work has significant implications for improving the safety and efficiency of power line maintenance, reducing the need for human intervention in hazardous environments. Peng’s research bridges computer vision, machine learning, and field robotics, demonstrating practical impact in real-world industrial applications. His contributions are recognized as foundational for advancing autonomous robotic systems in complex outdoor settings, making him a notable figure in the field of intelligent inspection robotics.
Research Focus
Key Achievements
Top Papers
- 1