Xuanhao Huang
Papers
1
Total Citations
2
H-Index
1
About
Xuanhao Huang’s research focuses on advancing autonomous mobile robot (AMR) navigation, with a particular emphasis on efficient path planning in constrained industrial environments. His major contribution lies in developing a novel method for extracting the shortest Dubins path between initial and final positions, especially over short distances—a scenario where traditional approaches often struggle with computational overhead. By streamlining the selection from the six Dubins curve types, his work directly improves real-time decision-making for AMRs in factory settings, enhancing operational efficiency and reducing energy consumption. His 2023 paper, “An Efficient Method for Extracting the Shortest Path from the Dubins Set for Short Distances,” has already garnered attention, with 2 citations signaling early impact in the field. Huang’s research addresses a critical bottleneck in robotics: balancing optimality with computational speed. His work is particularly notable for its practical applicability, offering a scalable solution for logistics and manufacturing automation. As AMRs become integral to Industry 4.0, Huang’s contributions promise to accelerate their deployment by making path planning faster and more reliable.
Research Focus
Key Achievements
Top Papers
- 1