Current Issue : April - June Volume : 2017 Issue Number : 2 Articles : 6 Articles
A comparative analysis between several methods to describe outdoor panoramic images is presented.Themain objective consists in\nstudying the performance of these methods in the localization process of a mobile robot (vehicle) in an outdoor environment, when\na visual map that contains images acquired from different positions of the environment is available. With this aim, we make use\nof the database provided by Google Street View, which contains spherical panoramic images captured in urban environments and\ntheir GPS position.Themain benefit of using these images resides in the fact that it permits testing any novel localization algorithm\nin countless outdoor environments anywhere in the world and under realistic capture conditions. The main contribution of this\nwork consists in performing a comparative evaluation of different methods to describe images to solve the localization problem\nin an outdoor dense map using only visual information. We have tested our algorithms using several sets of panoramic images\ncaptured in different outdoor environments. The results obtained in the work can be useful to select an appropriate description\nmethod for visual navigation tasks in outdoor environments using the Google Street View database and taking into consideration\nboth the accuracy in localization and the computational efficiency of the algorithm....
Networked navigation system (NNS) enables a wealth of new applications where real-time estimation is essential. In this paper,\nan adaptive horizon estimator has been addressed to solve the navigational state estimation problem of NNS with the features of\nremote sensing complementary observations (RSOs) and mixed LOS/NLOS environments. In our approach, it is assumed that RSOs\nare the essential observations of the local processor but suffer from random transmission delay; a jump Markov system has been\nmodeled with the switching parameters corresponding to LOS/NLOS errors. An adaptive finite-horizon group estimator (AFGE)\nhas been proposed, where the horizon size can be adjusted in real time according to stochastic parameters and random delays.\nFirst, a delay-aware FIR (DFIR) estimator has been derived with observation reorganization and complementary fusion strategies.\nSecond, an adaptive horizon group (AHG) policy has been proposed to manage the horizon size. The AFGE algorithm is thus\nrealized by combining AHG policy and DFIR estimator. It is shown by a numerical example that the proposed AFGE has a more\nrobust performance than the FIR estimator using constant optimal horizon size....
To achieve the wind sail-assisted function of the unmanned surface vehicle (USV), this work focuses on the design problems of the\nsail-assisted USV intelligent control systems (SUICS) and illustrates the implementation process of the SUICS. The SUICS consists\nof the communication system, the sensor system, the PC platform, and the lower machine platform. To make full use of the wind\nenergy, in the SUICS, we propose the sail angle of attack automatic adjustment (Sail 4A) algorithm and present the realization flow\nfor each subsystem of the SUICS. By using the test boat, the design and implementation of the SUICS are fulfilled systematically.\nExperiments verify the performance and effectiveness of our SUICS. The SUICS enhances the intelligent utility of sustainable wind\nenergy for the sail-assisted USV significantly and plays a vital role in shipping energy-saving emission reduction requirements\nissued by International Maritime Organization (IMO)....
In this study, an efficient navigation control method of mobile robot is proposed. The proposed navigation control\nmethod consists of behavior manager, toward goal behavior, and wall-following behavior. According to the relative position\nbetween the mobile robot and the environment, the behavior manager switches to determine toward goal behavior\nor wall-following behavior of mobile robot. A novel recurrent fuzzy cerebellar model articulation controller based on an\nimproved dynamic artificial bee colony is proposed for performing wall-following control of mobile robot. The proposed\nimproved dynamic artificial bee colony algorithm uses the sharing mechanism and the dynamic identity update to\nimprove the performance of optimization. A reinforcement learning method is adopted to train the wall-following control\nof mobile robot. Experimental results show that the proposed method obtains a better navigation control than\nother methods in unknown environment....
After the anti-collision facility construction of Wanzhou Yangtze River Highway\nBridge, the conditions of navigation in bridge area are complex. In order to study the\nnavigation conditions of the reach and layout optimization measures, ensuring the\nsafety of the ship navigation test has been carried out on the ship model navigation\nin the bridge area. According to the requirements of the maximum safety limit of the\nship model test, the paper puts forward the best route, the control method and the\ndifficulty of navigation through the analysis of the test results, and finally gives the\nrecommendations and suggestions....
The Global Positioning System (GPS) signals are used for navigation and positioning purposes by a diverse set of users. As a part\nof GPS modernization effort L5 has been recently introduced for better accuracy and availability service. This paper intends to\nstudy and simulate the GPS L1/L5 signal in order to fulfill the following two objectives. The first aimis to point out some important\nfeatures/differences between current L1 (whose characteristics have been fairly known and documented) and new L5 GPS signal for\nperformance evaluation purpose.The second aim is to facilitate receiver development, which will be designed and assembled later\nfor the actual acquisition of GPS data. Simulation has been carried out for evaluation of correlation properties and link budgeting\nfor both L1 and L5 signals. The necessary programming is performed in Matlab....
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