Kenji Ban
Papers
1
Total Citations
4
H-Index
1
About
Kenji Ban’s research centers on mobile robotics, computer vision, and autonomous navigation, with a particular focus on enabling robots to perceive and move through their environments using minimal hardware. His most-cited work introduces a method for estimating a mobile robot’s ego-motion and detecting obstacle depth through optical flow analysis, using only a single monocular camera. By distinguishing between planar flow—motion across flat surfaces—and normal optical flow from obstacles, Ban developed a pattern-matching approach that allows robots to infer depth and avoid collisions without expensive sensors. This contribution, published in 2009, has garnered 4 citations and remains a foundational reference for researchers working on low-cost, vision-based navigation systems. Ban’s work is notable for its elegant fusion of motion estimation and obstacle detection in a unified framework, addressing a core challenge in field robotics. His research continues to influence the development of lightweight, real-time perception algorithms for autonomous ground vehicles, particularly in environments where computational resources are limited.
Research Focus
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Top Papers
- 1