We use geomorphology as the setting, to present insights connecting Bayesian optimization for sequential experimental design, with semantic information acquired using robotics and AI. A key novelty in our approach is the use of physics engines commonly used in robotics and computer gaming, to run ensemble dynamical simulations on rock particles extracted from 3D maps reconstructed using aerial imagery. Our mapping pipeline for geomorphological analysis uses structure from motion (SfM) and deep learning on close-range aerial imagery to estimate spatial distributions of rock traits (diameter... Read more about The Annotation Game: Towards Collaborative Science with Humans, Robots, and AI (spotlight and poster)