Yizhao Deng

Papers

Total Citations

H-Index

About

Yizhao Deng is a researcher in robotics and autonomous navigation, with a primary focus on path planning algorithms for mobile robots. His most cited work, "Improved RRT global path planning algorithm based on Bridge Test" (2023), has garnered 64 citations, reflecting its impact on enhancing the efficiency and safety of rapidly-exploring random tree (RRT) algorithms. Deng’s major contribution lies in integrating the Bridge Test—a technique originally used for sampling narrow passages—into the RRT framework, significantly improving path quality and convergence speed in complex environments. This innovation addresses critical challenges in real-world robotic navigation, such as obstacle avoidance and computational efficiency. Beyond this, Deng’s research explores adaptive sampling strategies and multi-robot coordination, aiming to bridge the gap between theoretical algorithm design and practical deployment. His work is particularly notable for its application in autonomous vehicles and warehouse logistics, where reliable path planning is essential. With a growing citation record and a focus on scalable, robust solutions, Yizhao Deng is establishing himself as a promising voice in the field of intelligent robotics, offering practical tools for safer and more efficient autonomous systems.