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About

Xiujuan Lei is a computational intelligence researcher whose work centers on swarm optimization algorithms and autonomous robot navigation. With a career spanning over a decade, Lei has made significant contributions to solving one of robotics' most fundamental challenges: enabling mobile and aerial robots to efficiently plan optimal paths through complex, constrained environments. Lei's most influential work introduced the Intelligent Water Drops (IWD) algorithm to air robot path planning, drawing inspiration from natural river dynamics to tackle global optimization problems — a paper that garnered 52 citations and established her as a pioneer in nature-inspired computing for robotics. She further extended this research by applying the Artificial Bee Colony (ABC) algorithm to dynamic mobile robot path planning (38 citations) and developing a novel second-order oscillating Particle Swarm Optimization approach with sophisticated boundary constraint mechanisms (27 citations). A recurring theme throughout her portfolio is addressing the notorious "local optimum trap" in Particle Swarm Optimization, with Lei proposing innovative hybrid orthogonal and perturbation-based solutions. Her comprehensive surveys on swarm intelligence applications in robot path planning demonstrate her commitment to synthesizing this rapidly evolving field for broader audiences, cementing her reputation as both an innovator and educator in intelligent optimization research.