Rosalind Robertson
25 posts















What some companies mistake for progress , hiring people to teach robots to fold laundry in controlled spaces is only the first step; real autonomy needs verified, place-based truth. For @openmind_agi we’re doing exactly that: collecting ground-truth topology for real environments so robots learn to act where humans actually live and work. The data matters: where buildings sit, where roads and alleys run, the locations of entrances and storefronts, pockets of severe GPS drift, Wi-Fi availability and signal contours, surface types and obstacle density not aggregated map tiles, not heuristic labels, but verifiable, timestamped observations tied to on-site reality. This is not Google Maps; it’s the difference between a sketch and a living atlas that a robot can trust to navigate, manipulate, and complete tasks reliably. When a home robot learns to fold laundry or a delivery robot finds a back door, those capabilities come from grounding perception in reality repeated, proven examples that become the substrate of OM1’s embodied intelligence. In short: walking the world = acquiring the ground truth that turns simulated competence into dependable autonomy.






















