Daniel Delgado Bellamy

University of the West of England, Bristol Robotics Laboratory

Papers

Total Citations

H-Index

About

Daniel Delgado Bellamy is a researcher at the intersection of assistive robotics, human-robot interaction (HRI), and machine learning, with a focus on ensuring safety and personalization in robotic systems. His most cited work, "Safety Assessment Review of a Dressing Assistance Robot" (2021, 20 citations), critically evaluates traditional hazard analysis methods—such as HAZOP and STPA—within the context of assistive robotics. Bellamy highlights how the high dimensionality and human factors uncertainty inherent in these applications challenge conventional safety assurance, proposing novel adaptations to improve coverage and reliability. This contribution is pivotal for developing trustworthy robots that physically interact with vulnerable users. Additionally, his 2019 paper on "Collaborative HRI and Machine Learning for Constructing Personalised Physical Exercise Databases" explores how human-robot collaboration can generate tailored exercise regimens, leveraging machine learning to adapt to individual needs. While less cited, this work underscores his commitment to user-centered design. Bellamy’s research is particularly notable for bridging rigorous safety engineering with adaptive, human-aware robotics, offering practical pathways for deploying assistive technologies in healthcare and rehabilitation settings. His insights are valuable for students and engineers aiming to build safe, personalized robotic assistants.