Xinxin Jiang

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About

Xinxin Jiang is a prominent researcher in the field of mobile robotics and intelligent optimization algorithms, with a particular focus on path planning and autonomous navigation. Their most influential work, "Mobile Robot Path Planning Based on Improved Ant Colony Algorithm" (2023), addresses critical limitations in traditional ant colony optimization (ACO) methods, including susceptibility to local optima, low search efficiency, and poor convergence. By introducing the LACO algorithm, Jiang has significantly advanced the smoothness and reliability of robot trajectories in complex environments. This contribution has garnered 5 citations, reflecting its growing impact on both theoretical algorithm design and practical robotic applications. Jiang’s research bridges the gap between nature-inspired metaheuristics and real-world autonomous systems, offering robust solutions for dynamic obstacle avoidance and efficient route planning. Their work is particularly valuable for students and engineers developing intelligent mobile platforms, as it provides a clear framework for enhancing ACO-based navigation. With a strong foundation in swarm intelligence and computational geometry, Xinxin Jiang continues to shape the future of autonomous robotics through innovative algorithmic improvements.