William Eaton

About

William Eaton is a leading researcher in human-robot collaboration (HRC) and industrial automation, with a focus on making robotic systems accessible, safe, and adaptive for small and medium-sized enterprises (SMEs). His work bridges the gap between advanced robotics and practical manufacturing needs, particularly in mass customization and symbiotic human-robot teams. Eaton’s most cited paper, “Towards industrial robots as a service (IRaaS)” (119 citations), introduces a flexible, business-model-driven approach to lowering barriers for SMEs. He has also made significant contributions to safety and intention recognition, with his EEG-based arm movement intention recognition study (113 citations) enhancing collaborative safety. His Force/Torque-based learning for object manipulation (75 citations) advances adaptive robot behavior, while his recent incremental learning approach to detecting muscular fatigue (2023) addresses operator well-being in prolonged HRC tasks. Earlier work on autonomous vehicle systems (2014) demonstrates his breadth in networked autonomy. With over 300 total citations, Eaton’s research is shaping the future of agile, human-centered manufacturing.

Research Focus

Key Achievements

Top Papers

1. 1
   Towards industrial robots as a service (IRaaS): Flexibility, usability, safety and business models

   119 citations · 2022
2. 2
   EEG based arm movement intention recognition towards enhanced safety in symbiotic Human-Robot Collaboration

   113 citations · 2021
3. 3
   Improving human robot collaboration through Force/Torque based learning for object manipulation

   75 citations · 2021
4. 4
   An Incremental Learning Approach to Detect Muscular Fatigue in Human– Robot Collaboration

   11 citations · 2023
5. 5
   Development of a generic network enabled autonomous vehicle system

   7 citations · 2014

Key Collaborators

Contact & Links