A DDS-based middleware for quality-of-service and high-performance networked robotics.

Abstract

Social robots must adapt to dynamic environments, human interaction partners and challenging new stringent tasks. Their inner software is usually distributed and should be designed and deployed carefully because slight changes in the robot’s requirements can have an important impact not only on the existing source code but also on the resulting performance at run-time. This paper describes our experiences in the design and implementation of a lightweight middleware for networked robotics called Nerve, which guarantees the scalability and quality-of-service (QoS) requirements for this kind of real-time software. Its benefits have been proved through its use in two key components of the cognitive system of a social robot: a visual attention mechanism and a robot learning by imitation control architecture. Nerve makes use of existing patterns for networked applications along with the recent Data Distribution Service specification (DDS), where different QoS have been applied carefully to achieve the best performance of the target robot.