Jingjing Zhang

China University of Geosciences, Nanjing University of Information Science and Technology

Papers

Total Citations

H-Index

About

Jingjing Zhang’s research bridges robotics, computer vision, and intelligent automation, with a focus on enhancing the precision and adaptability of autonomous systems. Her most cited work, "Trajectory Planning of a Six-DOF Robot Based on a Hybrid Optimization Algorithm" (2016, 5 citations), tackles the challenge of optimizing robotic motion by integrating ant colony, particle swarm, and genetic algorithms. This hybrid approach improves efficiency in industrial tasks like spot welding, demonstrating her ability to solve complex kinematic problems with computational intelligence. In "CH-Marker: A Color Marker Robust to Occlusion for Augmented Reality" (2017, 3 citations), Zhang advances AR and robot navigation by designing fiducial markers that maintain reliable detection even when partially obscured—a critical improvement for real-world deployment. Her earlier work, "Status recognition of isolator based on SmartGuard" (2013, 3 citations), applies computer vision to smart substation inspection robots, enabling automated recognition of isolator states via homography matrices. This contribution supports safer, more efficient sequence control in power infrastructure. Across these studies, Zhang’s work consistently merges algorithmic innovation with practical engineering, earning her recognition for advancing robotic trajectory planning, robust visual markers, and intelligent inspection systems.