Parallel Learning Architecture of micROS Powering the Ability of Life-Long Autonomous Learning

As the most important infrastructure of robotic platforms, robot operating system is playing an important role to improve autonomy and intelligence of robots and unmanned systems. In this paper, a parallel learning architecture of micROS supporting life-long autonomous learning is presented. It is built to power a wide variety of robots with the ability of contextual adaptation. In addition, two core concepts guiding the design of micROS are also presented. One concept is the actor, which is the control abstraction of robot behaviors. The other concept is the semantic situation abstracting the dataflow in micROS. Some important techniques including collective behavior control and ad hoc wireless networks, are also described in this paper.