Experimentation and analysis of time series data from multi-path robotic environment

Abstract

Autonomous mobile robots are increasingly used in many application areas. In most applications, they have to explore and gather knowledge about the environment they are deployed in. These robots transfer real time data about the environment continuously. This paper discusses a set of experiments that have been carried out to simulate various robotic environments. A robot attached with four sensors is used to collect information about the environment as the robot moves in multiple straight line paths. Time series data collected from these experiments are clustered using data mining techniques. Experimental results show clustering accuracies vary depending on the number of clusters formed.