Max Robotics — Global Service Robot Directory + US Certification

About

Kosei Isomoto is a robotics researcher focused on advancing service and human support robots for real-world environments. His work spans autonomous waiter systems, object recognition, and human-robot interaction, with a particular emphasis on making robots more perceptive and responsive in dynamic settings like homes and cafeterias. His most cited paper, "Autonomous Waiter Robot System for Recognizing Customers, Taking Orders, and Serving Food" (2024, 6 citations), demonstrates a complete pipeline for service robots in hospitality. He has also contributed to object position interpretation through visual prompting methods like Set of Mark (SoM), enabling robots to understand spatial relationships for tasks such as tidying and tray storage. Isomoto’s lightweight hand-waving action recognition system, using reservoir computing, addresses the need for efficient human intention recognition in crowded spaces. Additionally, his work on optimizing object placement with two-dimensional irregular packing algorithms improves the efficiency of human support robots in organizing tasks. As a member of the Hibikino-Musashi@Home team, he has developed open-source tools and dataset generators for robot vision training, contributing to the broader robotics community. With a growing citation record and a focus on practical, deployable solutions, Isomoto is shaping the next generation of socially aware service robots.