Architecture-driven self-adaptation and self-management in robotics systems

Abstract

We describe an architecture-centric design and implementation approach for building self-adapting and self-managing robotics systems. The basis of our approach is the concept of meta-level components, which facilitate adaptation and management of application-level components. Our approach applies two key enhancements to the traditional usage of meta-level components: (1) we utilize three distinct, specialized meta-level components for the three fundamental activities of a robotics system: sensing, computation, and control, and (2) we allow meta-level components to themselves be monitored, managed and adapted by other (higher layer) meta-level components. In this way, our approach flexibly supports adaptive layered architectures of arbitrary depth, the specification of arbitrary system adaptation policies, and the provision of intelligent facilities for constructing adaptation plans on-the-fly. We showcase our approach using a team of autonomous mobile robots that engage in a leader-follower scenario and experience a wide variety of failures, activating distinct recovery mechanisms.