An open architecture for on-board intelligent diagnosis and recovery in autonomous robots

Abstract

A way to improve the performance in autonomous robots is adding intelligence to control systems avoiding hardware redundancy and inopportune mission abortion. In this paper, we present a distributed architecture supporting diagnosis and control of autonomous robots with the purpose of assisting the operator or piloting system in managing fault detection, risk assessment, and recovery plans under uncertainty. The architecture is generic, open and modular consisting of a decision module, intelligent modules, and robot piloting modules. The decision module is the architecture core requesting intelligent modules for diagnosis and recovery action based on data obtained from robot piloting modules