Yiwei Zhang

Papers

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About

Yiwei Zhang is a robotics and autonomous systems researcher whose work focuses on three-dimensional path planning for unmanned aerial vehicles (UAVs), particularly rotary-wing flying robots. Zhang's research addresses one of the most challenging problems in autonomous robotics: enabling aerial vehicles to navigate complex, obstacle-rich environments such as mountainous terrain safely and efficiently. Zhang's most notable contribution is the development of a hybrid path planning framework that intelligently combines classical algorithms with nature-inspired optimization techniques. Their 2016 paper, which has garnered 17 citations, introduced an innovative fusion of the A* algorithm with an improved artificial potential field method specifically adapted for 3D environments — a significant advancement over traditional 2D approaches. Building on earlier work from 2015, Zhang also explored integrating ant colony algorithms with artificial potential fields, demonstrating a consistent commitment to hybrid, bio-inspired computational strategies for solving complex spatial navigation problems. Together, these contributions reflect Zhang's dedication to making autonomous aerial navigation more robust and applicable to real-world scenarios. Their research serves as a valuable reference for engineers and scientists working on drone autonomy, search-and-rescue systems, and intelligent UAV mission planning in challenging three-dimensional terrains.