A cell-based approach for evolutionary component repositories for intelligent service robots

Abstract

Self-growing software is a software system that has the capability of evolving its functionalities and configurations by itself based on dynamically monitored situations. Self-growing software is especially necessary for intelligent service robots, which must have the capacity to monitor their surrounding environments and provide appropriate behaviors for human users. Intelligent service robots often face problems that cannot be resolved with the current conventional software technology. To support self-growing software for intelligent service robots, the SemBots project is developing a cell-based distributed repository system that allows robots and developers transparently to share robot functionalities. To accomplish the creation of evolutionary repositories, we invented the concept of a cell, which is a logical group of distributed repositories based upon the functionalities of components. In addition, it is also a unit for the evolutionary growth of the components within the repositories. In this thesis, we describe the requirements and architecture of the cell-based repository system for self-growing software. We also present a prototype implementation and experiment of the repository system. Through the cell-based repositories, we achieve improved performance of self-growing actions for robots and efficient sharing of components between robots and developers.