Haoquan Mo

Shenzhen University

Papers

1

Total Citations

44

H-Index

1

About

Haoquan Mo is a leading researcher in robotics and autonomous systems, with a primary focus on simultaneous localization and mapping (SLAM) technologies. His work critically addresses the rapid evolution of LiDAR sensors, particularly the transition from traditional mechanical to emerging solid-state LiDARs. Mo’s most influential contribution is his 2023 comparative analysis of SLAM algorithms for these two LiDAR types, which has already garnered 44 citations. This study provides essential benchmarks and performance evaluations, helping the robotics community understand the trade-offs between cost, accuracy, and reliability as low-cost solid-state LiDARs gain market dominance. By systematically testing algorithms like LOAM and Cartographer on both sensor platforms, Mo’s work offers practical guidance for deploying SLAM in real-world applications, from autonomous vehicles to service robots. His research is notable for bridging a critical gap in the literature, enabling engineers to make informed decisions about sensor selection and algorithm optimization. Mo’s contributions are shaping the next generation of navigation systems, making him a key figure in advancing affordable, robust autonomous technology.

Research Focus

Key Achievements

1
H-Index
1
Papers
44
Total Citations
44
Avg Citations/Paper
🏆 Most Cited Paper
Comparative Analysis of SLAM Algorithms for Mechanical LiDAR and Solid-State LiDAR
44 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Shenzhen University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago