Zhiyang Jia

Papers

Total Citations

H-Index

About

Zhiyang Jia is a robotics researcher whose work focuses on advancing autonomous navigation through intelligent path planning algorithms. His primary research areas include mobile robot motion planning, artificial potential fields, and reinforcement learning for robotic systems. Jia’s most impactful contribution is his work on the Improved Hybrid A* Algorithm, which addresses critical limitations in traditional path planning by reducing unnecessary steering actions and improving obstacle clearance. This paper has garnered 40 citations, reflecting its significance in the field. He further advanced the state of the art with his Hybrid Bidirectional Rapidly Exploring Random Tree (H-BRRT) algorithm, which integrates reinforcement learning to overcome the randomness and slow convergence inherent in conventional RRT methods. This work, cited 12 times, demonstrates his innovative approach to combining classical planning techniques with modern machine learning. Jia’s research is particularly valuable for real-world applications where robots must navigate complex, cluttered environments efficiently and safely. His contributions help bridge the gap between theoretical path planning algorithms and practical deployment in autonomous systems.