Junsong Zhang

Chongqing University of Posts and Telecommunications

Papers

Total Citations

H-Index

About

Junsong Zhang is a researcher whose work lies at the intersection of robotics, autonomous navigation, and intelligent control systems. His most impactful contributions center on enhancing motion planning algorithms, particularly through the optimization of the Rapidly-exploring Random Tree (RRT) framework. In his highly cited 2021 work, "Robot Arm Path Planning Based on Improved RRT Algorithm," Zhang tackled critical limitations of traditional RRT methods—namely, high randomness, excessive computational complexity, and suboptimal path generation. By fusing the RRT algorithm with artificial potential field techniques, he developed a more efficient and deterministic approach to robotic arm path planning, enabling smoother, safer, and more optimal trajectories in complex environments. This innovation has garnered 10 citations, reflecting its practical value for industrial automation and service robotics. Zhang’s research is especially relevant for students and engineers seeking to bridge the gap between theoretical path planning and real-world robotic applications. His work continues to influence the development of more intelligent, adaptive, and computationally efficient systems for autonomous manipulation.