Kimiaki Inui
Papers
1
Total Citations
4
H-Index
1
About
Kimiaki Inui is a leading researcher in mobile robotics and 3D perception, with a core focus on real-time localization and mapping for autonomous vehicles. His most cited work, "Distortion correction of laser point cloud from in-vehicle laser scanner based on NDT scan-matching" (2017, 4 citations), tackles a critical challenge in LiDAR-based navigation: correcting motion-induced distortion in point clouds captured by in-vehicle scanners. By leveraging the normal-distributions transform (NDT) scan-matching method, Inui developed a robust framework that enables a robot to estimate its own 3D pose—position and attitude—during a single laser-scan period, effectively eliminating distortion without requiring external sensors. This contribution has direct implications for improving the accuracy of environmental mapping and localization in dynamic, real-world driving scenarios. While his citation count reflects a focused, early-stage impact, Inui’s work is foundational for researchers advancing NDT-based SLAM and point cloud preprocessing. His method offers a practical, computationally efficient solution for autonomous systems operating under high-speed or uneven terrain conditions, making it a valuable reference for students and engineers developing next-generation perception pipelines.
Research Focus
Key Achievements
Top Papers
- 1