Yatao Shi

Tianjin University of Science and Technology

Papers

Total Citations

H-Index

About

Yatao Shi is a researcher specializing in computational intelligence and robotics, with a primary focus on path planning optimization for autonomous mobile systems. His most cited work, "Based on adaptive improved genetic algorithm of optimal path planning" (2022), addresses a critical challenge in robotics: overcoming the tendency of simple genetic algorithms to converge on suboptimal, local solutions. Shi’s key contribution lies in developing an improved adaptive genetic algorithm that enhances global search capability. Specifically, he introduced a discontinuous continuity method for population initialization, which diversifies the starting solutions and prevents premature convergence. This innovation enables more efficient and reliable robot navigation in complex environments. With 4 citations, his work is gaining traction among researchers tackling optimization problems in autonomous systems. Shi’s research bridges theoretical algorithm design and practical robotic applications, offering a robust framework for real-time path planning. His approach is particularly valuable for students and engineers seeking to implement adaptive, nature-inspired algorithms in mobile robotics, making his contributions a stepping stone for advancements in intelligent automation and autonomous navigation.