ChaoShu Dai

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About

ChaoShu Dai is a researcher in robotics and computational intelligence, with a primary focus on path planning and optimization for mobile robots. Their most notable contribution lies in the development of a genetic algorithm-based approach for planar mobile robot navigation, where they innovatively transformed grid map models into two-dimensional matrices and introduced a mobile operator with probabilistic attributes. This work, published in 2023 and garnering 11 citations, proposed a novel genetic coding method based on matrix row and column numbers, using the reciprocal of path distance as a fitness function to enhance route efficiency. Dai’s research bridges the gap between evolutionary computation and practical robotics, offering scalable solutions for autonomous navigation in complex environments. Their work is particularly impactful for students and researchers exploring bio-inspired algorithms in robotics, as it demonstrates how genetic algorithms can be tailored to solve real-world spatial problems. With a growing citation record, Dai continues to contribute to the advancement of intelligent systems, making their research a valuable resource for those interested in the intersection of optimization theory and robotic applications.