Swarm underwater acoustic 3D localization: Kalman vs Monte Carlo

Two three-dimensional localization algorithms for a swarm of underwater vehicles are presented. The first is grounded on an extended Kalman filter (EKF) scheme used to fuse some proprioceptive data such as the vessel's speed and some exteroceptive measurements such as the time of flight (TOF) sonar distance of the companion vessels. The second is a Monte Carlo particle filter localization processing the same sensory data suite. The results of several simulations using the two approaches are presented, with comparison. The case of a supporting surface vessel is also considered. An analysis of the robustness of the two approaches against some system parameters is given

Decision Support System for smart urban management: resilience against natural phenomena and aerial environmental assessment

A new concept of Decision Support System (DSS) is presented. It is able to account for and support all phases of the risk analysis process: event forecast, prediction of reliable and accurate damage scenarios, estimate of their impact on Critical Infrastructures (CI), estimate of the possible consequences. It also provides an estimate of the consequences in terms of service degradation and of impact on citizens, on urban area and on production activities, essential for the mitigation of the adverse events. It can be used in two different modes, either in an operational mode (on a 24/7 basis) or in a simulation mode to produce risk analysis, setting up synthetic natural hazards and assessing the resulting chain of events (damages, impacts and consequences). Among the various possible external data sources an aerial, drone based one is presented. The system may capture both thermal and visual images of CI, processing them into 3D models or collect chemical pollutants concentrations for the monitoring of dangerous air quality due to catastrophic events such as volcano eruptions or large fires. The obtained models and the chemical data can be easily displayed within the framework of the DSS

Urban Air Pollutant Monitoring through a Low-Cost Mobile Device Connected to a Smart Road

Air pollutant monitoring is a basic issue in contemporary urban life. This paper describes an approach based on the diffused use of low-cost sensors that can be mounted on board urban vehicles for more abundant and distributed measures. The system exchanges data, exploiting a “Smart Road” infrastructure, with a central computing facility, the CIPCast platform, a GIS-based Decision Support System designed to perform real-time monitoring and interpolation of data with the aim of possibly issuing alarms with respect to different town areas. Experimental data gathering in the Rome urban area and subsequent processing results are presented. Algorithms for data fusion among different simulated monitoring systems and interpolation of data for a geographically denser map were utilised. Thus, in the framework of the Smart Road, protocols for data exchange were designed. Finally, air pollutant distribution maps were produced and integrated into the CIPCast platform. The feasibility of a full system architecture from the sensors to the real-time pollutant maps is shown

HARNESS: A ROBOTIC SWARM TO EXPLORE AND PROTECT UNDERWATER CULTURAL HERITAGE

International audienceThis work describes an underwater robotic system to be used for exploration, fruition and surveillance of underwater cultural heritage.This system is based on a number of cheap autonomous underwater vehicles (AUV) organised on the swarm rules. Its development is currently in progress in our laboratory in the framework of the HARNESS project (Human telecontrolled Adaptive Robotic NEtwork of SensorS) . The project aims at the realization of an underwater multi body robotic system able to perform tasks in a fast and reliable way. The key points of the HARNESS project are: the development of a novel underwater acoustic channel with very high performances in routing and data throughput capacities and the design of a reliable swarm rule-based control system with an interface towards a supervisor operator acting as a priority definition arbiter. The project includes a demonstration with a limited number of physical vehicles and with a larger number of simulated ones.In a swarm the members operate with a common objective, sharing the job workload; the lack of one member can be easily taken care of by redistributing the job among the others. This feature is especially useful if we consider, as application the discovery and the surveillance of submarine archeological sites. Moreover a swarm can be considered as a single body, offering the advantage of a simple way of interfacing with the human end-users and overcoming the problem of the control of a large number of individuals. The geometrical distribution of the members of this system is flexible and adaptable to the task and environment characteristics. In the underwater world the physical medium makes the acoustical channels as the most convenient one, since electromagnetic waves are rapidly damped. The acoustical technology has limited performances too, being affected by a fast decrease in the signal bandpass (limited carried frequency) as the distance increase. The swarm technology allow to avoid this drawback by a suitable and intelligent spatial distribution of transmission nodes (the swarm members themselves), allowing the exploitation of ultra-high frequencies and an enhanced data transmission through logical and physical routing. One of the aims of the project is the study and implementation of different behaviors in the swarm, to generate a collective shaping as a response to environment stimula and to modifiy of the communication parameters in order to maximize the performance of the system.The swarm control must balance the different requests of the operator (e.g. modify the mission task), the swarm needs and the single members management (e.g. obstacle avoidance, loss of communication link).The result is the selection of collective behaviours that must be compatible with all the before mentioned conditions.. The methods currently under evaluation to this aim include neural network techniques, fuzzy logic and genetic algorithms.In the swarm there is no central brain, mainly because of the excess needs in band pass requested by such a brain. Instead each individual must possess an intelligent local control system capable to manage its choices according to the choices of the neighbours on the basis of the available data. Data coherence along the swarm, being affected by the the position of the member and by the data propagation speed is also a research topic.The foreseen applications of this underwater swarm are the safeguard of the underwater cultural heritage in terms of: exploration of submerged sites, searching for possible new relics, surveillance known sites against damage, realization of a remote museum facility where tourists and archaeologists can explore underwater sites without “getting wet”