Kei Kakimuma
Papers
1
Total Citations
29
H-Index
1
About
Kei Kakimuma is a robotics researcher whose work focuses on multi-robot perception and human-robot interaction in dynamic outdoor environments. His most significant contribution lies in developing laser-based pedestrian tracking systems that enable multiple mobile robots to collaboratively detect and follow human subjects in real-world settings. In his landmark 2012 paper, "Laser-Based Pedestrian Tracking in Outdoor Environments by Multiple Mobile Robots," Kakimuma introduced an occupancy-grid-based method for detecting pedestrians from laser scan images, combined with Kalman filtering and global data association to maintain consistent tracks across robot teams. This work, which has garnered 29 citations, addresses the critical challenge of robust human tracking outside controlled indoor spaces—a key requirement for applications like autonomous navigation, search-and-rescue, and social robotics. By demonstrating how distributed sensor networks can overcome occlusion and environmental noise, Kakimuma has helped lay the groundwork for safer, more responsive robot systems that operate alongside people. His research continues to influence the development of cooperative perception algorithms, making him a notable figure in the intersection of field robotics and human-aware autonomy.
Research Focus
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Top Papers
- 1