Max Robotics — Global Service Robot Directory + US Certification

About

Galoget Latorre’s research sits at the intersection of intelligent built environments, robotic construction, and human-machine interaction, with a focus on making physical spaces safer, more responsive, and more autonomous. In one of their most impactful works, Latorre developed a facial-identity and -expression recognition system that uses TensorFlow to confirm or negate physical and computational actuations in smart environments—a foundational contribution to context-aware, human-centered automation. This paper has garnered 8 citations and demonstrates a novel approach to merging computer vision with ambient intelligence. Latorre also advanced construction robotics through the design of a novel robotic gripper for automated scaffolding assembly, addressing one of the most hazardous tasks in the industry; this work, with 7 citations, has direct implications for reducing workplace fatalities. Further, their high-resolution intelligence implementation, rooted in Design-to-Robotic-Production and -Operation (D2RP&O) strategies developed at TU Delft, integrates differentiated, function-specialized components with extended ambient intelligence. With a portfolio that bridges theoretical frameworks and deployable systems, Latorre’s work is shaping the future of intelligent, robotic-assisted environments.