Planning Under Uncertainty

When only part of the world is known to the robot, it must understand how unseen space is structured so that it can reason about the goodness of trajectories that leave known space. For instance (and as seen above), whether the agent enters the classroom may depend on how likely it is that the classroom leads to the goal. Planning under uncertainty can be incredibly difficult, making even seemingly simple predictions about the future is fraught with challenges, since it can be difficult to predict what lies just around the corner, much less one-hundred meters away. Much of the research in the RAIL Group involves dealing with some type of uncertainty and coming up with clever ways to incorporate learned experience without sacrificing guarantees on completeness or violating trust.