Papers
2
Total Citations
42
H-Index
2
About
Guanling Wang is a leading researcher in mobile robotics, with a primary focus on developing advanced path planning algorithms that balance efficiency, optimality, and safety. Their most significant contribution is the APF-IRRT* algorithm (2022), which ingeniously integrates the Artificial Potential Field method with Informed RRT* to overcome the latter's limitations in narrow or cluttered environments. This work, which has garnered 36 citations, demonstrates how combining heuristic forces with sampling-based planners can dramatically improve convergence speed and path quality for autonomous navigation. Wang also explored the use of metaheuristic optimization, as seen in their 2018 work on robot path planning using the Tree Growth Search Algorithm (TGSA) with three-order Bézier curves, achieving smoother trajectories. Their research directly addresses real-world challenges in mobile robot deployment, from warehouse logistics to autonomous driving. By bridging theoretical algorithm design with practical implementation, Wang’s work has become essential reading for researchers and engineers working on intelligent navigation systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Robot path planning based on TGSA and three-order bezier curve6 citations · 2018