jilu Guo

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About

Dr. Jilu Guo is a leading researcher in intelligent robotics and autonomous navigation, with a primary focus on advancing mobile robot path planning. Their most impactful work addresses critical limitations in the artificial potential field (APF) method—a foundational approach for real-time obstacle avoidance. In their highly cited 2020 paper, "Dynamic path planning of mobile robot based on artificial potential field" (27 citations), Dr. Guo proposed a novel improved APF algorithm that solves the persistent challenges of gravity imbalance, local minima entrapment, and oscillatory trajectories. By reconstructing the potential field function model and introducing a pose threshold gain mechanism, their work enables smoother, more reliable, and dynamically adaptive navigation for mobile robots in complex environments. This contribution is vital for applications ranging from warehouse automation to autonomous vehicles. Dr. Guo’s research bridges theoretical robotics with practical deployment, offering robust solutions that enhance both safety and efficiency in autonomous systems. Their work continues to influence subsequent studies in intelligent control and real-time path optimization.