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.

Comparing System Optimum-based and User Decision-based Traffic Models in an Autonomous Transport System

Abstract: The paper introduces a framework to perform the demand management and route planning tasks of a highly developed transport system managing scheme, assuming an autonomous transport system. Two types of autonomous transport system managing models have been introduced. In case of the first model, the assigned number of trips is assumed to be the modified variable related to the optimization problem. In case of the second model, the decision process is directly influenced by the travel prices defined by the optimization method. These approaches represent different demand management strategies. The first model aims to directly assign the incoming user demands to the system, while the second procedure lets the users make the decision. However, in the second case the system can strongly influence the users’ choices through the values of the travel prices. Accordingly, it seems to be a reasonable assumption that the firstly presented model has significantly higher efficiency in distributing the load on the network. On the other hand, the method of the second model would be much more tolerable and acceptable from a social point of view. Therefore, the aim of the paper is to introduce the developed models and to compare their efficiencies.

Secure Communication and Implementation for a Chaotic Autonomous System

Abstract: In this paper, a three-dimensional chaotic autonomous system is presented. The stability of the equilibrium and the conditions of the Hopf bifurcation are studied by means of nonlinear dynamics theory. Then, the circuit of chaotic system is structured out in Multisim platform by the unit circuit. The chaotic system is applied to secure communications by linear feedback synchronization control. All simulations results performed on three-dimensional chaotic autonomous system are verified the applicable of secure communication. DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.4003

Employing Fuzzy Logic for Navigation and Control in an Autonomous Mobile System

Abstract: The Space Exploration Initiative of the United States of America includes plans for unmanned missions to Mars to investigate and examine the terrain and soil samples for a future manned mission. In particular, uncharted obstacles may interfere with the maneuvering of the system. It will be nearly impossible to control the system using radio hookups, as the delays are extensive, and therefore an intelligent autonomous system is necessary. Due to inherent uncertainties in the problem and the wish to design a system that uses intuitive approaches to navigation problems, we have chosen to explore the use of fuzzy logic in autonomous mobile vehicles.

Deep Learning Inference at the Edge for Mobile and Aerial Robotics

Abstract: Deep learning inference is an established element for autonomous robots especially in the domain of safety, security, and rescue applications. Autonomous functions based on deep learning inference are considered the spearhead of such robots paving the way for increased demand in onboard computational resources and performance accuracy. Edge computing is steadily improved in terms of computational power but at the same time artificial neural networks are becoming even more deep and complex. To this end, the right selection between the on-board hardware platform and an efficient deep neural network is considered a challenging tradeoff issue in the autonomous system design. In this paper, we investigate the current landscape in deep learning inference at the edge by evaluating the requirements, challenges and available solutions for service-oriented architectures in the safety, security, and rescue domain. Current research directions and best optimization practices are discussed, enriched with computational and accuracy comparisons providing necessary insights for optimal system design.