Ni Xiong

Papers

Total Citations

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About

Ni Xiong is a researcher specializing in mobile robotics and intelligent path planning, with a particular focus on ant colony optimization (ACO) algorithms for dynamic environments. Their major contributions lie in advancing the efficiency and adaptability of ACO-based navigation systems, addressing critical challenges such as slow convergence, poor global search capability, and real-time obstacle avoidance. Xiong’s most cited work, "Mobile Robot Path Planning Based on Time Taboo Ant Colony Optimization in Dynamic Environment" (2021, 28 citations), introduces a novel time taboo strategy that significantly improves path planning in environments with unknown, time-varying obstacles. A second influential paper, "Path Planning of Mobile Robot Based on Adaptive Ant Colony Optimization" (2021, 7 citations), proposes an adaptive initial pheromone distribution to enhance early-stage search performance. Together, these studies have garnered over 35 citations, reflecting their impact on the field of autonomous navigation. Xiong’s work is particularly notable for bridging theoretical optimization algorithms with practical robotic applications, offering scalable solutions for dynamic and unpredictable settings. Their research continues to inspire advancements in swarm intelligence and mobile robot autonomy.