Lecture
Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.
This lecture explores learning models for solving belief-driven mobile manipulation tasks in open environments. It covers topics such as continuous error checking, recovery, and actions like leaping, grasping, dragging, climbing, throwing, and stacking. The instructor presents a technical approach involving Aspect Transition Graphs, Active Belief Planner, and Landscape of Attractors. Additionally, the lecture discusses Intrinsically Motivated Structure Learning, habituation thresholds, and examples of stacking experiments.