Akinori Ueno

About

Akinori Ueno is a leading researcher in robotics and autonomous navigation, with a focus on enabling robots to operate intelligently in human-centered environments. His most influential work, "Robot navigation in corridor environments using a sketch floor map" (2004, 32 citations), introduced a groundbreaking approach that allows robots to navigate using simple, user-drawn sketch maps—similar to building floor plans—without requiring precise metric data or detailed obstacle information. This innovation significantly lowers the barrier for human-robot interaction, making navigation systems more accessible and practical for real-world deployment. Ueno has also made notable contributions to cognitive robotics, particularly in integrating learning and abstraction. His research on "Cooperation of cognitive learning and behavior learning" (2003) and "Learning of the way of abstraction in real robots" (2003) addresses the fundamental challenge of how robots can simultaneously learn state representations and behavioral policies, as well as how to autonomously abstract relevant information from complex environments—a core aspect of the frame problem. Through these works, Ueno has advanced the fields of robot learning and human-robot collaboration, demonstrating how robots can adapt flexibly to dynamic settings while relying on intuitive, user-friendly inputs.

Research Focus

Key Achievements

Top Papers

1. 1
   Robot navigation in corridor environments using a sketch floor map

   32 citations · 2004
2. 2
   Cooperation of cognitive learning and behavior learning

   3 citations · 2003
3. 3
   Learning of the way of abstraction in real robots

   3 citations · 2003

Key Collaborators

Contact & Links