Analysis of multimodal time series data of robotic environment

Abstract

Autonomous mobile robots equipped with an array of sensors are being increasingly deployed in disaster environments to assist rescue teams. The sensors attached to the robots send multimodal time series data about the disaster environments which can be analyzed to extract useful information about the environment in which the robots are deployed. A set of data mining tasks that effectively cluster various robotic environments have been investigated. The effectiveness of these data mining techniques have been demonstrated using an available robotic dataset. The accuracy of the proposed technique has been measured using a manual reference cluster set.