Max Robotics — Global Service Robot Directory + US Certification

About

Naohiro Fukumura is a pioneering researcher in robotics and neural network learning, best known for his foundational work on goal-directed, sensory-based navigation for mobile robots. His landmark 1994 paper, "Learning goal-directed sensory-based navigation of a mobile robot," with 62 citations, established a core framework for enabling robots to learn and execute navigation tasks using sensory feedback rather than pre-programmed paths. This work was brought to life through physical experiments with the mobile robot YAMABICO, as detailed in his 1997 paper (18 citations), where he demonstrated how self-organizing internal representations could emerge from learning. Fukumura further advanced the field by exploring attractor dynamics for sensory-motor systems and developing a modular auto-encoder architecture for integrating diverse information streams. He also contributed to inverse dynamics learning in real robots through a forward-propagation learning rule, addressing how neural networks can learn control models without backpropagation. Though his citation counts reflect a focused, specialized audience, Fukumura’s impact lies in his early, hands-on demonstrations of neural network-based robot learning, bridging theory and physical experimentation in a way that inspired subsequent work in autonomous robotics and embodied cognition.