Papers
1
Total Citations
9
H-Index
1
About
Jiguang Wu is an emerging researcher in the field of robotics, with a primary focus on motion planning and control for mobile robotic systems operating in complex, obstacle-filled environments. His most cited work introduces a novel planning and tracking approach for mobile robotic arms, addressing the critical challenge of autonomous object manipulation in cluttered spaces. Specifically, Wu developed an improved APF-RRT* algorithm that enhances the efficiency of random tree node selection, enabling smoother and more reliable motion planning. This contribution, published in 2023, has already garnered 9 citations, signaling growing interest from the robotics community. Wu’s research bridges the gap between path planning and real-time tracking, offering practical solutions for industrial automation, search-and-rescue, and service robotics. By optimizing both the planning and execution phases, his work helps mobile robotic arms navigate obstacles while maintaining precision in grasping tasks. As a researcher whose early career output is already being recognized, Jiguang Wu is establishing himself as a promising voice in the advancement of autonomous robotic manipulation and intelligent motion control.
Research Focus
Key Achievements
Top Papers
- 1