Creating autonomous robots that can assist humans in situations of daily life is a great challenge for machine learning. While this aim has been a long standing vision of robotics, artificial intelligence, and the cognitive sciences, we have yet to achieve the first step of creating robots that can accomplish a multitude of different tasks, triggered by environmental context or higher level instruction. Despite the wide range of machine learning problems encountered during the automatic acquisition of new abilities for robots, we have yet to fulfill the promise that modern learning approaches offer in this context.
Creating complex learning systems that endow robots with the ability to autonomously learn new skills serves both as source of new ideas and benchmark for machine learning approaches. It may among the most promising ways to take robots out of the research labs and bring them into real-world environments.