Max Robotics — Global Service Robot Directory + US Certification

About

Takuma Yoneda is a robotics researcher whose work sits at the intersection of dexterous manipulation, human-robot collaboration, and embodied AI. His major contributions span three key areas: advancing real-world dexterous manipulation through structured benchmarks and winning competition entries, pioneering shared autonomy systems that blend human and robot control, and integrating large language models with robotic reasoning. Yoneda’s most-cited paper, “Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation” (2021, 24 citations), established rigorous evaluation standards for the TriFinger platform, while his “Statler” papers (2023–2024, 31 combined citations) introduced state-maintaining language models that enable robots to reason about action histories—a novel dimension in embodied AI. His “To the Noise and Back: Diffusion for Shared Autonomy” (2023, 17 citations) proposes a diffusion-based framework for collaborative control, offering a fresh approach to the classic shared autonomy problem. Notably, Yoneda led the winning submission to the Real Robot Challenge (2021), a three-phase dexterous manipulation competition, demonstrating practical impact through motion planning and grasp strategies. His work on cloud-accessible robotic clusters further promotes reproducible research, making him a key contributor to open, scalable robotics experimentation.