Papers
14
Total Citations
223
H-Index
7
About
Bao Pang is a robotics researcher whose work spans swarm robotics, simultaneous localization and mapping (SLAM), and autonomous exploration strategies. With a portfolio of highly cited publications, Pang has established a strong reputation in developing intelligent algorithms that enhance the collective behavior and navigational capabilities of robotic systems. Among Pang's most significant contributions is pioneering work on random walk methods for swarm robot exploration, including an improved strategy published in 2019 that has garnered 49 citations, alongside a 2021 follow-up study with 40 citations — together forming a foundational body of work on search efficiency in multi-robot systems. Pang has also made notable advances in SLAM technology, particularly adapting both 2D and 3D mapping techniques for search-and-rescue (SAR) environments, with a three-dimensional visual SLAM paper earning 43 citations. Additional contributions include multi-robot cooperative SLAM frameworks, bio-inspired optimization algorithms such as bacterial foraging, and self-organized task allocation modeled on social insect behavior. More recently, Pang has extended into deep learning-based visual SLAM for dynamic indoor environments. Collectively accumulating over 210 citations, Pang's research meaningfully bridges bio-inspired computation and real-world autonomous robotics, offering practical solutions for disaster response and complex environment navigation.
Research Focus
Key Achievements
Top Papers
- 1A Swarm Robotic Exploration Strategy Based on an Improved Random Walk Method49 citations · 2019
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- 8Analysis of Random Walk Models in Swarm Robots for Area Exploration6 citations · 2019
- 9Deep learning-based visual SLAM for indoor dynamic scenes4 citations · 2025
- 10Real-Time Object Recognition Based on NAO Humanoid Robot3 citations · 2018