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About

Bing Sun is a robotics and autonomous systems researcher whose work centers on path planning, autonomous underwater vehicles (AUVs), and intelligent inspection robotics. With a career spanning over a decade, Sun has made significant contributions to solving complex navigation challenges in unstructured environments, particularly beneath the ocean's surface where dynamic forces such as ocean currents demand fundamentally different algorithmic approaches than those used in ground-based robotics. Sun's most influential work, "Complete Coverage Path Planning of Autonomous Underwater Vehicle Based on GBNN Algorithm" (2018), has accumulated 122 citations, establishing him as a notable voice in AUV autonomy research. His earlier studies on artificial potential fields and velocity synthesis (2015, 59 citations) addressed the critical challenge of integrating ocean current modeling into real-time AUV navigation, a problem with meaningful implications for underwater exploration and marine operations. Sun has also explored multi-AUV cooperative behaviors, examining how teams of underwater vehicles can coordinate hunting strategies under environmental disturbance. More recently, Sun has extended his expertise to land-based robotics, developing improved A* and bio-inspired neural network algorithms for intelligent substation inspection robots, bridging underwater and industrial automation domains. His body of work reflects a consistent focus on making autonomous systems more robust, efficient, and deployable in real-world, dynamically challenging environments.