Max Robotics — Global Service Robot Directory + US Certification

About

Yusuke Iwasawa is a robotics and machine learning researcher whose work sits at the intersection of robot learning, human-robot interaction, and autonomous manipulation. His research primarily focuses on Learning from Demonstration (LfD), meta-learning, and the deployment of general-purpose service robots in real-world environments. Iwasawa's early contributions explored how user interfaces shape the quality of robot learning, notably through his 2018 work leveraging Virtual Reality to make demonstration-based training more intuitive and effective — a paper that has garnered 13 citations. This theme of practical, human-centered robot learning carries through his involvement in the World Robot Challenge 2020, where his team developed data-driven approaches enabling mobile manipulators to tidy household environments amid real-world complexity, accumulating 13 citations across related publications. His 2020 work on safe meta-imitation learning addresses a critical challenge in robot autonomy — enabling robots to generalize to novel tasks while remaining uncertainty-aware. More recently, his 2024 "Self-Recovery Prompting" system, developed for RoboCup@Home 2023, demonstrates his forward-looking integration of foundation models into robust, adaptable service robotics. Iwasawa's body of work reflects a consistent drive to bridge theoretical robot learning with deployable, competition-tested systems.