Max Robotics — Global Service Robot Directory + US Certification

About

Norimasa Kobori is a researcher at the forefront of embodied AI, robotics, and intelligent transportation systems. His work spans reinforcement learning for robotic control, computer vision for object manipulation, and novel sensing for autonomous driving. In his foundational 2002 paper, Kobori pioneered the use of a nested actor/critic algorithm to control a double inverted pendulum, an early demonstration of reinforcement learning’s potential for adaptive robotics. More recently, he has driven practical innovation in industrial automation, proposing a novel encoded marker system for working robots—a solution designed for robust detection under blur and varied poses, directly addressing challenges in competitions like the Amazon Picking Challenge. Kobori also contributes to the future of autonomous vehicles, evaluating mobile environments for vehicular visible light communication using event cameras. His most impactful work, however, is his leadership in the 9th AI City Challenge (2025, 16 citations), which attracted 245 teams from 15 countries and advanced real-world AI applications in transportation, industrial automation, and public safety. Through this challenge and his technical contributions, Kobori has demonstrated a consistent commitment to bridging the gap between algorithmic research and deployable, real-world robotic and vision systems.