Banghe Wu

Nanjing University of Science and Technology

Papers

Total Citations

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About

Banghe Wu is a leading researcher in autonomous robotic exploration, with a focus on active SLAM (Simultaneous Localization and Mapping) and frontier-based navigation. His work addresses the fundamental challenge of enabling robots to efficiently and autonomously explore unknown environments. Wu’s most influential contribution is his integrated approach to active exploration, detailed in his highly cited 2020 paper “Frontier Detection and Reachability Analysis for Efficient 2D Graph-SLAM Based Active Exploration” (36 citations). This work pioneered the use of Cartographer’s submap-based SLAM with geometrically co-aligned submaps for efficient frontier detection, combined with reachability analysis to guide robot motion. He further advanced the field with the “Ada-Detector” (2022, 13 citations), an adaptive RRT-based frontier detector that enables real-time, incremental exploration without pre-set parameters. Most recently, his “Concave-Hull Induced Graph-Gain” method (2023, 8 citations) solved a critical limitation of RRT-based exploration—its inability to detect all frontiers due to expansion disturbances—by using concave hulls to model drivable areas. Wu’s work has been recognized for its practical impact on robust, uninterrupted exploration in real-world robotics, making him a key figure in the development of next-generation autonomous navigation systems.