Chaowen Xiong

Chongqing University of Posts and Telecommunications

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About

Chaowen Xiong is a robotics and intelligent algorithms researcher whose work centers on autonomous navigation, motion planning, and bio-inspired optimization techniques. Xiong has made notable contributions to the field of robot path planning, developing innovative algorithmic solutions that address fundamental limitations in classical approaches. Most prominently, Xiong's 2020 work on 3D path planning using an improved ant colony algorithm has garnered 23 citations, demonstrating meaningful uptake within the robotics research community. Complementing this, Xiong proposed a hybrid IACO-SFLA algorithm that strategically combines an improved ant colony algorithm with the shuffled frog leaping algorithm — a creative fusion designed specifically to overcome critical weaknesses in standard ant colony optimization, including slow convergence, low computational efficiency, and susceptibility to local optimal solutions. This hybrid approach reflects Xiong's broader research philosophy of leveraging the strengths of multiple bio-inspired metaheuristics to produce more robust and practical planning systems. Collectively, Xiong's contributions advance the development of smarter, more reliable autonomous robots capable of navigating complex real-world environments — research with significant implications for industrial automation, service robotics, and intelligent systems engineering.