Max Robotics — Global Service Robot Directory + US Certification

About

Elisabet Batlle is a researcher whose work sits at the intersection of computer vision, robotics, and 3D reconstruction, with a particular focus on autonomous underwater systems and environmental mapping. Her most significant contribution lies in advancing Simultaneous Localization and Mapping (SLAM) techniques for underwater vehicles, notably demonstrated in her 2008 paper on Visual SLAM for large-scale seabed acquisition, which has garnered 19 citations and introduced a novel approach using stereo cameras and Extended Kalman Filters to enable autonomous underwater vehicles to simultaneously map and navigate complex seabed environments. This work addresses one of the most challenging problems in marine robotics, where GPS is unavailable and conditions are highly dynamic. Beyond underwater systems, Batlle has made meaningful contributions to 3D registration techniques for industrial quality control, exploring how visual inspection can detect surface and volumetric imperfections in manufactured components. Her work on image and surface registration for six-degrees-of-freedom robot and camera pose estimation further demonstrates her breadth across robotic perception. Early work on physical agent simulation for underwater robots reflects a consistent research trajectory spanning over a decade. Her contributions offer valuable tools for both marine exploration and automated manufacturing inspection.