About

Norimichi Ukita is a leading researcher in autonomous navigation, human-robot interaction, and trajectory prediction, with a focus on safety-critical and human-centric applications. His work bridges probabilistic modeling and real-time robotics, most notably through the development of FlowChain, a normalizing flow-based model for fast, accurate trajectory prediction in autonomous vehicles and social robots (42 citations). Ukita has also pioneered methods to reduce passenger stress in robotic wheelchairs, introducing collision prediction for blind occluded regions and using physiological indices to measure and enhance comfort during autonomous navigation. His early work on robot navigation via eye pointing (10 citations) laid groundwork for intuitive human-robot interfaces. With contributions spanning from behavior representation systems that communicate wheelchair actions to passengers, to future-guided imitation learning for long action sequences, Ukita’s research consistently addresses the dual challenges of computational efficiency and human comfort. His impact is evident in both theoretical advances in probabilistic density estimation and practical systems for assistive robotics, making him a key figure in developing robots that are not only autonomous but also socially aware and passenger-friendly.

Research Focus

Key Achievements

5
H-Index
6
Papers
83
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Fast Inference and Update of Probabilistic Density Estimation on Trajectory Prediction
42 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: Toyota Technological Institute, Advanced Telecommunications Research Institute International, Nara Institute of Science and Technology

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago