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.

Modern industry requires an improved motor performance and the permanent magnet brushless DC (BLDC) motors are especially appropriate for applications that require a high level of accuracy and performance. The advanced control strategies when applied into BLDC motor drive systems may further enhance their performance. However, these methods are relatively complex and computationally intensive, which may hamper the implementation. Fuzzy logic control algorithm has been developed in this investigation and embedded into a commercially available motion control system for the position control of BLDC motors. BLDC motor drives offered by PicoMotion Inc. and Motion Control Framework software platform have been selected for the experiments due to their compactness, flexibility and the open hardware and software concept they have been created upon. The obtained comparative results with respect to the built in PI control law have confirmed that the implementation of more advanced control strategies on inexpensive hardware and software platforms, nowadays available on the market for the control of BLDC motors, can be practically feasible and can enhance their performance.