Embodiment independent manipulation through action abstraction

The adoption of robots for service tasks in natural environments calls for the use of sensors to allow manipulation of objects under imperfect environment knowledge and the use of knowledge transfer from humans. This paper addresses these challenges by proposing a new abstraction architecture for embodiment independent sensor-based control of manipulation. The aim is to address three specific challenges: hardware independent control of manipulation, use of sensors to alleviate problems of complexity and uncertainty of the environment, and ease of transferring knowledge over different embodiments through a hierarchical abstract representation of manipulation skills. The proposed abstraction architecture is demonstrated for hardware independence and failure detection on two different manipulator platforms.