Tamas Bates

Delft University of Technology, Technical University of Munich

Papers

Total Citations

145

H-Index

About

Tamas Bates is a leading researcher at the intersection of robotics, human-robot interaction, and ergonomics. His work focuses on enabling safe, efficient, and physically intuitive cooperation between humans and robots. Bates’s major contributions include developing computational models that predict ergonomic risk during physical human-robot tasks and optimizing robot action sequences to minimize human strain. His most cited work, “Predicting and Optimizing Ergonomics in Physical Human-Robot Cooperation Tasks” (55 citations), introduces a novel framework for incorporating ergonomic assessments into the planning of bi-manual cooperative manipulation. He has also pioneered methods for capturing realistic human behaviors using virtual reality, as seen in his 2017 paper on simultaneous learning and recognition of everyday activities (48 citations), which facilitates the transfer of human models to robotic systems. Additionally, Bates has advanced real-time vision-based 3D modeling for humanoid navigation in unknown environments and developed systems for cooperative object manipulation with contact changes. His research is distinguished by its practical focus on real-world applications, from manufacturing to assistive robotics, and his work has garnered significant attention for its potential to reshape how robots physically collaborate with humans.