Bang Cheng

National University of Defense Technology

Papers

1

Total Citations

22

H-Index

1

About

Bang Cheng has made significant contributions to computer vision and robotics, particularly in the domain of real-time 3D object tracking. His research focuses on leveraging LiDAR sensor technology to enhance motion tracking capabilities for indoor environments, addressing critical challenges in navigation, autonomous systems, and military applications. His most cited work, "Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor" (2017, 22 citations), demonstrates a breakthrough in achieving real-time visualization and tracking of moving objects using VLP-16 3D LiDAR point cloud data. This paper has been influential in advancing practical tracking solutions that balance computational efficiency with accuracy, serving as a foundation for subsequent work in dynamic environment perception. Cheng’s research bridges the gap between theoretical computer vision algorithms and real-world sensor deployment, offering scalable approaches for robotics and autonomous navigation. His work continues to inspire further exploration into LiDAR-based tracking systems, with potential applications spanning from industrial automation to intelligent transportation.

Research Focus

Key Achievements

1
H-Index
1
Papers
22
Total Citations
22
Avg Citations/Paper
🏆 Most Cited Paper
Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor
22 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: National University of Defense Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago