Neural net tracking control of a mobile platform in robotized wireless sensor networks

Abstract

In the recent years sensor networks have emerged as an effective tool for monitoring environments that are large in size and have complex topology. They have been successfully applied to solve various problems such as monitoring of different environmental indicators, detection of floods and fires, temperature control in office buildings, to collect information about the health status of hospitalized patients, to monitor the activity of some species and many others. Based-on the wireless communications the unification of the sensor modules can be implemented as a wireless sensor network (WSN). A newly observed trend is the inclusion of mobile robots into the WSN structure. The present paper describes a work-in-progress aiming to build laboratory prototype of a robotized hybrid WSN. The latter can be used for various distributed control experiments over the network structure and its efficiency. A robotized wireless sensor node has been designed and its functionality has been experimentally tested using an advanced trajectory tracking control algorithm. The proposed robotic node consists itself of a mobile robot platform integrated with a wireless sensor node. The latter has been implemented with a Tiva C Series TM4C1294NCPDT LaunchPad evaluation board equipped with TI Sensor Hub and WiFi Booster Pack. The mobile robot platform is based on the iRobot Create additionally upgraded with an on-board control system built in with gumstix verdex pro XL6P embedded microprocessor.