Perception, control, data, and hardware to enable robots to dynamically manipulate physical objects and systems for useful tasks like assembly, repair, and transport.

Learning-based control methods that allow robots to safely and robustly interact with the physical world, supporting adaptive behavior, human guidance, and operation in novel environments.

Foundation models that enable robots to perform complex physical tasks, including precision assembly and force-mediated behavior, by combining data-driven learning with principled models.

Building mobile robots that have semantic understanding of their surroundings and can navigate diverse environments, such as factories, cities and homes.

How the impact of robot integration in daily life – including workplaces, homes, and other shared spaces – affects human attitudes and actions.