Bing-Jui Ho

Carnegie Mellon University, Aptiv (United States)

Papers

2

Total Citations

90

H-Index

2

About

Bing-Jui Ho is a robotics researcher whose work centers on advancing Simultaneous Localization and Mapping (SLAM) for complex, three-dimensional environments. His key contributions lie in developing novel mapping representations and optimization techniques that make SLAM more robust and practical. Ho’s most impactful work introduces the Virtual Occupancy Grid Map (VOG-map), a globally deformable map built from local submaps. This innovation allows pose graph SLAM systems to correct accumulated drift via loop closures while preserving critical free space information for path planning, a significant step forward for autonomous navigation in 3D spaces. His second major contribution addresses a critical challenge in underwater robotics: degeneracy in SLAM. Ho proposed degeneracy-aware factors that enable SLAM systems to detect and handle scenarios where sensor measurements provide insufficient constraints, preventing catastrophic localization failures. With his top two papers accumulating 46 and 44 citations respectively, Ho’s work has been recognized for directly tackling the practical limitations of SLAM in real-world, often unstructured environments. His research is particularly valuable for applications requiring long-term autonomy, from underwater exploration to aerial and ground robotics, where robust state estimation is paramount.

Research Focus

Key Achievements

2
H-Index
2
Papers
90
Total Citations
45
Avg Citations/Paper
🏆 Most Cited Paper
Virtual Occupancy Grid Map for Submap-based Pose Graph SLAM and Planning in 3D Environments
46 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Carnegie Mellon University, Aptiv (United States)

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago