Very recently, the paradigm of the Internet of Mobile Things (IoMT), in which smart things can be moved or can move autonomously whilst remaining accessible and controllable remotely, has been the object of a great attention in the research community. In this context, the paper proposes and investigates a novel framework to support both the management and the collaboration of Mobile Smart Objects (MSOs) considered as terrestrial and aerial drones (i.e., UAVs, UGVs). MSOs are equipped with embedded sensors and/or actuators and can move autonomously always remaining connected, accessible and controllable. The proposed framework allows the programming and management of smart drones and the coordination of teams of drones according to a mission-oriented paradigm. Coordination is dynamically enabled by specific executive parameters and system conditions (i.e., residual energy, computational power, abilities offered by specific on board sensors). To evaluate the effectiveness and the reliability of the proposed framework, a real testbed was created using off-the-shelf drones.
A Mission-Oriented Coordination Framework for Teams of Mobile Aerial and Terrestrial Smart Objects
Pace P;Aloi Gianluca;Caliciuri G;Fortino Giancarlo
2016-01-01
Abstract
Very recently, the paradigm of the Internet of Mobile Things (IoMT), in which smart things can be moved or can move autonomously whilst remaining accessible and controllable remotely, has been the object of a great attention in the research community. In this context, the paper proposes and investigates a novel framework to support both the management and the collaboration of Mobile Smart Objects (MSOs) considered as terrestrial and aerial drones (i.e., UAVs, UGVs). MSOs are equipped with embedded sensors and/or actuators and can move autonomously always remaining connected, accessible and controllable. The proposed framework allows the programming and management of smart drones and the coordination of teams of drones according to a mission-oriented paradigm. Coordination is dynamically enabled by specific executive parameters and system conditions (i.e., residual energy, computational power, abilities offered by specific on board sensors). To evaluate the effectiveness and the reliability of the proposed framework, a real testbed was created using off-the-shelf drones.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.