Bolei Chen
Papers
4
Total Citations
32
H-Index
4
About
Bolei Chen is an emerging researcher specializing in autonomous robotics, with a particular focus on autonomous exploration strategies and socially-aware robot navigation. His work addresses fundamental challenges in enabling unmanned aerial vehicles (UAVs) and ground robots to intelligently navigate and map unknown environments without human intervention. Chen's most significant contributions include STExplorer (2023), his most-cited work with 15 citations, which introduced a hierarchical exploration strategy incorporating spatio-temporal awareness to overcome limitations in existing cost estimation and information gain frameworks. His follow-up work, EMExplorer (2023), pioneered the application of episodic memory and deep reinforcement learning (DRL) to autonomous exploration, combining Voronoi domain conversion with invalid action masking for more efficient robotic decision-making. His earlier research on space-heuristic navigation and occupancy map prediction further demonstrates his systematic approach to the exploration problem. Beyond pure exploration, Chen has broadened his scope to human-robot interaction through his SocialNav-FTI framework (2024), which applies field-theory-inspired principles to ensure robots navigate social spaces with courtesy and cultural compliance. Collectively accumulating over 30 citations, Chen's growing body of work positions him as a promising contributor to next-generation intelligent robotics systems.
Research Focus
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Top Papers
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