Hokuto Fujii
Papers
1
Total Citations
3
H-Index
1
About
Hokuto Fujii is a robotics researcher focused on autonomous navigation for mobile robots and unmanned ground vehicles (UGVs) operating in challenging, uneven terrains. His key contributions lie in developing decision-making frameworks that enable robots to navigate unknown environments without relying on global map information. In his most cited work, "Mobile Robot Decision-Making Based on Offline Simulation for Navigation over Uneven Terrain" (2018), Fujii proposed a novel action decision framework that uses locally observed terrain features and offline simulation to help a UGV choose optimal paths at forks or complex junctions. This approach addresses a critical bottleneck in field robotics: how to make reliable navigation decisions with limited prior knowledge. While his citation count is modest (3 citations for this paper), the work represents a foundational step toward more autonomous and robust off-road navigation systems. Fujii’s research is particularly relevant for applications in agriculture, disaster response, and planetary exploration, where terrain is unpredictable and pre-mapped routes are unavailable. His work exemplifies the intersection of simulation-based planning and real-world robotic autonomy.
Research Focus
Key Achievements
Top Papers
- 1