Max Robotics — Global Service Robot Directory + US Certification

About

Carlos Ricolfe-Viala is a researcher whose work spans computer vision, robotics, and human-robot interaction, with a particular focus on bridging foundational perception challenges and real-world automation applications. His most influential contribution examines the often-overlooked impact of autofocus lenses on camera calibration processes, a study that has garnered 20 citations and highlights the limitations of traditional pin-hole models in achieving true reprojection accuracy — a critical concern for robust robotics and computer vision systems. His earlier work on industrial robot programming and UPnP service orchestration (11 citations) demonstrated a forward-thinking approach to smart factory integration, connecting robots with Ethernet-enabled devices such as vision systems, laser scanners, and PLCs to create more intelligent manufacturing environments. Ricolfe-Viala has also advanced robot perception through efficient image-labelling methods that minimize human intervention in training convolutional neural networks, and has explored developmental neuro-robotics by creating databases for visual finger-based numerical recognition. More recently, his inventive application of robotics to sports science — using a robot to identify the sweet spot of padel rackets — showcases his versatility and creativity. His body of work reflects a researcher committed to practical, interdisciplinary solutions at the intersection of automation, perception, and intelligent systems.