Atsushi Umemura
Papers
1
Total Citations
2
H-Index
1
About
Atsushi Umemura is a robotics researcher specializing in autonomous navigation and motion planning for mobile robots operating in unstructured environments. His work focuses on developing robust path planning algorithms that account for pose estimation errors, particularly in rough terrain where traditional methods fail. His most-cited paper, "Robust Path Planning Against Pose Errors for Mobile Robots in Rough Terrain" (2018), introduces a novel approach that integrates uncertainty in robot localization into the planning process, enabling safer and more reliable traversal over uneven ground. While his citation count is modest, this work addresses a critical gap in field robotics—ensuring that robots can navigate real-world conditions without relying on perfect sensor data. Umemura’s contributions are valuable for applications in search-and-rescue, planetary exploration, and agricultural robotics, where terrain variability and localization drift are common challenges. His research highlights the importance of bridging theoretical planning with practical robustness, making him a notable figure in the niche but vital area of rough-terrain navigation.
Research Focus
Key Achievements
Top Papers
- 1