Papers
1
Total Citations
2
H-Index
1
About
Heng Yuxi is a researcher in computational intelligence and robotics, with a primary focus on optimization algorithms for autonomous navigation. Their most notable contribution is the development of an improved grey wolf optimization algorithm for mobile robot path planning, published in 2022. This work addresses critical challenges in robotic motion, specifically the slow convergence speed and high path cost associated with traditional optimization methods. By modifying the linear convergence factors within the grey wolf optimizer and establishing a two-dimensional obstacle avoidance model, Heng proposed a more efficient solution for generating optimal, collision-free trajectories. While their work is still in its early stages of dissemination, with 2 citations to date, it represents a meaningful step in the application of swarm intelligence to practical robotics problems. Heng’s research sits at the intersection of metaheuristic algorithms and autonomous systems, contributing to the broader effort of making robots more adaptive and efficient in complex environments. Their work is particularly relevant for students and researchers exploring nature-inspired optimization techniques for real-world engineering challenges.
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Top Papers
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