Takaaki Kojima
Papers
2
Total Citations
4
H-Index
2
About
Takaaki Kojima has made focused contributions to the field of autonomous robotics, particularly in the areas of multi-robot simultaneous localization and mapping (SLAM) and state estimation for unmanned aerial vehicles (UAVs). His work addresses fundamental challenges in enabling robots to perceive and navigate large-scale environments. In his research on multi-robot SLAM, Kojima developed a novel recursive least squares (RLS) algorithm for merging local maps constructed by individual robots into a coherent global map, a critical capability for collaborative robotic exploration. This approach leverages relative information between local maps, offering an efficient solution for large-scale mapping tasks. Additionally, Kojima has tackled the practical problem of robust position estimation for UAVs using Kalman Filters, specifically designing compensation mechanisms to handle unexpected or erroneous visual observations that can degrade estimation accuracy. While his most-cited papers each have 2 citations, reflecting a specialized technical audience, his work contributes to the foundational toolkit for deploying reliable multi-robot systems in real-world, unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Image-based position estimation of UAV using Kalman Filter2 citations · 2015