To make transfer to applications in everyday domains robots require the ability to cope with novelty, incomplete information, and uncertainty. In this talk I will describe a line of work carried out over ten years that provides methods to tackle this. I will examine two problems: object search and grasping. This requires the ability to reason and learn in open worlds and novel circumstances. The results are demonstrated in two robot systems, Dora and Boris. Dora is a robot for object search that plans in open worlds. The technical contribution is to achieve this by using assumptive planning and common-sense knowledge. Dora uses the same scheme to verify explanations in the face of failure. Boris is a robot that learns to grasp novel objects from a very small number of example grasps. The novel technical contribution in that instance is the use of products of experts to enable grasp transfer. If there is time I will briefly mention other work.