Continually Improving Robots
GHC 8102Abstract: General purpose robots should be able to perform arbitrary manipulation tasks, and get better at performing new ones as they obtain more experience. The current paradigm in robot learning involves training a policy, in simulation or directly in the real world, with engineered rewards or demonstrations. However, for robots that need to keep learning [...]
Parallelized Search on Graphs with Expensive-to-Compute Edges
GHC 6115Abstract: Search-based planning algorithms enable robots to come up with well-reasoned long-horizon plans to achieve a given task objective. They formulate the problem as a shortest path problem on a graph embedded in the state space of the domain. Much research has been dedicated to achieving greater planning speeds to enable robots to respond quickly [...]
Generative and Animatable Radiance Fields
Newell-Simon Hall 3305Abstract: Generating and transforming content requires both creativity and skill. Creativity defines what is being created and why, while skill answers the question of how. While creativity is believed to be abundant, skill can often be a barrier to creativity. In our team, we aim to substantially reduce this barrier. Recent Generative AI methods have simplified the problem for 2D [...]