Papers
10
Total Citations
135
H-Index
6
About
Shunbo Zhou is a leading researcher in robotics, specializing in multi-sensor fusion for simultaneous localization and mapping (SLAM), large-scale multi-robot coordination, and vision-based control. His most impactful work includes the development of the MARS-LVIG dataset (41 citations), a comprehensive multi-sensor aerial robotics benchmark that integrates LiDAR, visual, inertial, and GNSS data—advancing robust SLAM in challenging environments. Zhou also pioneered LTA-OM (34 citations), a long-term association LiDAR-IMU odometry and mapping framework, and NF-Atlas (18 citations), which introduces neural feature fields for large-scale LiDAR mapping. Beyond perception, he has made significant contributions to coordinating robot networks, proposing hierarchical frameworks for cooperative path planning in logistics and warehouse systems with hundreds to thousands of robots. His work on vision-based state estimation and trajectory tracking for car-like mobile robots addresses real-world challenges like wheel skidding and slipping. With over 130 total citations, Zhou’s research bridges theoretical advances and practical deployment, earning recognition for enabling reliable, scalable autonomy in aerial, ground, and multi-robot systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2LTA‐OM: Long‐term association LiDAR–IMU odometry and mapping34 citations · 2024
- 3NF-Atlas: Multi-Volume Neural Feature Fields for Large Scale LiDAR Mapping18 citations · 2023
- 4A Hierarchical Framework for Coordinating Large-Scale Robot Networks13 citations · 2019
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- 6Vision-Based Dynamic Control of Car-Like Mobile Robots8 citations · 2019
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