Task-directed configuration of networked robotic agents

Abstract

In this paper we present research aimed at exploring the configuration of robot architecture from robot components that are distributed about a network environment. The research is motivated by previous work focusing on representation and reasoning methods for modeling modular robotics systems. We look specifically at self-configuring networked robotic agents. The proposed model combines the notions of a task factory that generate task modules and a pool of modules representing robotics components such as sensors and effectors. A number of successively more complex scenarios are used to illustrate the concepts. These have been implemented and tested experimentally. The paper describes the experimental implementation.