Autonomous system (mathematics)

About: Autonomous system (mathematics) is a research topic. Over the lifetime, 1648 publications have been published within this topic receiving 38373 citations.

Network-Aware Server Placement for Highly Interactive Distributed Virtual Environments

Abstract: In distributed virtual environments, e.g., online gaming, collaborative designs and distributed military simulations, interactivity is one of the most important requirements. The users may notice serious degradations in quality of service when interacting in the virtual world if the response from the system is much slower than what they have experienced in real life. In this paper, we consider the problem of placing distributed servers in the network to reduce client-server communication latencies, which is termed the server placement problem. We proposed two new network-aware placement algorithms which take into account users' locations in the network and connectivity at the autonomous system level to determine good sites for servers. Extensive experiments with realistic network models showed that these new algorithms significantly outperform existing approaches that require full knowledge of network connectivity at the router-level topologies.

Inferring User Intention using Gaze in Vehicles

Abstract: Motivated by the desire to give vehicles better information about their drivers, we explore human intent inference in the setting of a human driver riding in a moving vehicle. Specifically, we consider scenarios in which the driver intends to go to or learn about a specific point of interest along the vehicle's route, and an autonomous system is tasked with inferring this point of interest using gaze cues. Because the scene under observation is highly dynamic --- both the background and objects in the scene move independently relative to the driver --- such scenarios are significantly different from the static scenes considered by most literature in the eye tracking community. In this paper, we provide a formulation for this new problem of determining a point of interest in a dynamic scenario. We design an experimental framework to systematically evaluate initial solutions to this novel problem, and we propose our own solution called dynamic interest point detection (DIPD). We experimentally demonstrate the success of DIPD when compared to baseline nearest-neighbor or filtering approaches.

Non-linear feedback control of a novel chaotic system

Abstract: From the classical Lu chaotic system a new simple three-dimensional autonomous system is derived, which exhibits a three-scroll chaotic attractor. An approach to control this novel attractor by non-linear feedback functions is proposed. The results obtained reveal that the trajectories of the chaotic attractor can be controlled to reach certain target periodic orbits or points. Finally, some numerical simulations are provided to show the effectiveness and feasibility of the controller design method developed.

Experiencing Self-adaptive MAS for Real-Time Decision Support Systems

Abstract: Hydrological phenomena are often very dynamic and depend on numerous criteria. The STAFF software is an adaptive model for flood forecast based on self-organizing multiagent systems. It is operational since 2002 in the Midi-Pyrenees region in France. The aim of this paper is to show the relevance of our approach to model complex natural systems by focusing on the results, architecture and self-organization mechanisms of a real world application. The main idea is to let the artificial system self-adapt towards the adequate model by confronting it to real data, thus ensuring that the resulting model represents reality. Moreover, since the MAS is constantly adapting, we obtain a dynamic and autonomous system that can take into account any future dynamics (strong perturbations, sensor breakdowns...) and able to provide decision-makers with usable information anytime.

Multisensor based fully autonomous non-cooperative collision avoidance system for UAVs

Abstract: Unmanned Aerial Vehicles will have a safe access to the Civil Airspace only when they will be able to avoid collisions even with non cooperative flying obstacles. Thus, they need to replace the capability of human eye to detect potential mid-air collisions with other airframes and the pilot experience to find an adequate avoidance trajectory. This thesis deals with development and test of a fully autonomous system devoted to avoidance of non cooperative intruders. In particular, it focuses on sensors, and processing logics and hardware, required on the unmanned system to acquire situational awareness. The study was carried out in collaboration with the Italian Aerospace Research Center within a research project named TECVOL, funded in the frame of National Aerospace Research Program. The performed activities covered all the steps in the development process from the analysis of requirements deriving from the application, to the real time implementation of designed logics. Designed prototype system is based on a multi-sensor architecture with a Ka-band pulsed radar as the main sensor, and four electro-optical cameras as aiding sensors. Proper logics and algorithms for real time sensor fusion have been developed, tested in off-line simulations, and later implemented on embedded systems to enable technology flight demonstration. Numerical results and flight data have shown the potential of the developed system. Also on the basis of the international scenario, this technology demonstration has gained a significant scientific value.