For robots to be effectively deployed in homes and settings where they will interact with novice users, they must empower users with accessible and understandable control over that robot. This control may manifest itself as a user directly teleoperating the robot, directing the means of collaboration, or appropriately leveraging the robot’s autonomy to perform novel tasks. To enable this, our work focuses on the design and evaluation of user-centered algorithms and approaches to give users’ greater control over an already autonomous and partially capable robot. We consider how to leverage pretraining prior to deployment, user-robot interaction histories, and in our ongoing work, generalist robot foundation models to empower novices to use a robot how and for the purposes they want.