Papers
3
Total Citations
22
H-Index
3
About
Ruoyu Xu is a robotics researcher specializing in trajectory planning and motion control for legged and rail-inspection robots. Their work focuses on overcoming the limitations of conventional optimization methods—such as slow response times and poor smoothness—by developing hybrid metaheuristic algorithms. Xu’s most notable contribution is the Hybrid Improved-Whale-Optimization–Simulated-Annealing Algorithm for quadruped robots, which simultaneously optimizes joint trajectory smoothness and movement time, achieving 10 citations since 2023. They also advanced rail-inspection robot autonomy through an Improved Penalty Function Simulated Annealing Particle Swarm Algorithm (8 citations) and an Improved Hybrid Polynomial Interpolation Algorithm (4 citations), both designed to reduce angular velocity and acceleration amplitudes during dynamic target tracking. With a cumulative citation count of 22 across their top papers, Xu’s research directly addresses real-world challenges in agile robotics, offering computationally efficient solutions for time-critical and high-precision applications. Their work is particularly relevant for students and engineers interested in bio-inspired optimization, swarm intelligence, and the practical deployment of autonomous inspection systems in constrained environments.
Research Focus
Key Achievements
Top Papers
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