A Framework for the Development of Robot Behavior

摘要

Biological organisms display an astonishing capability to learn new skills and adapt to dynamic environments that far outperforms any computer or robot system. This paper presents an approach to robot skill acquisition that takes concepts from developmental theory to structure the learning problem and provides a mechanism to gen-erate developmental schedules for a robot systems. The approach uses a developmental assembler to construct reusable and temporally extended actions in a sequence. All behavior is initially constructed from a set of in-nate control laws and events that delineate control deci-sions are derived from the pattern of (dis)equilibria on a working subset of sensorimotor policies. We show how this architecture can be used to accomplish se-quential knowledge gathering and representation tasks and provide examples of developmental learning using a quadrupedal walking robot.