Benshan Ma
Papers
1
Total Citations
17
H-Index
1
About
Benshan Ma is a rising researcher in robotics and autonomous navigation, with a primary focus on efficient path planning for mobile robots. His most-cited work introduces APF-RRT*, a novel hybrid algorithm that integrates artificial potential fields with the RRT* sampling-based planner. This method dramatically improves time efficiency—a critical bottleneck in real-world robotic applications where delays can compromise safety. By guiding the sampling process with a potential field, Ma’s approach reduces unnecessary exploration and accelerates convergence to near-optimal paths, achieving 17 citations since 2023 and demonstrating immediate relevance to the field. His contributions address a core challenge: balancing computational speed with path quality in dynamic environments. Ma’s work is particularly notable for its practical impact, offering a scalable solution for autonomous systems ranging from warehouse robots to self-driving vehicles. As a researcher, he exemplifies how algorithmic innovation can directly enhance robotic safety and responsiveness, making his research essential reading for students and engineers working on real-time motion planning.
Research Focus
Key Achievements
Top Papers
- 1