Health signal generation in the ORCA (Organic robot control architecture) framework

Abstract

This paper evaluates various information-theoretical methods for the generation of health signals in the Organic Robot Control Architecture (ORCA). Also a new method based on the joint probability distribution of signals is proposed. The results show that the new method is superior to the known ones for the studied worst-case artificial and real scenarios. As an example for the application of health signals in ORCA, an adaptable path planner is described which considers the health status of a partially damaged robot.