scholarly journals A Relative-Localization Algorithm Using Incomplete Pairwise Distance Measurements for Underwater Applications

2010 ◽  
Vol 2010 (1) ◽  
Author(s):  
Kae Y. Foo ◽  
Philip R. Atkins
Keyword(s):  
Pairwise Distance ◽  
Localization Algorithm ◽  
Distance Measurements ◽  
Relative Localization

scholarly journals Multi-UAV Area Coverage Based on Relative Localization: Algorithms and Optimal UAV Placement

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2400
Author(s):  
Ziyong Zhang ◽  
Xiaoling Xu ◽  
Jinqiang Cui ◽  
Wei Meng
Keyword(s):  
Quadratic Programming ◽  
Wide Band ◽  
Area Coverage ◽  
Localization Algorithm ◽  
Placement Problem ◽  
Position Information ◽  
Relative Localization ◽  
Coverage Control ◽  
Localization Algorithms ◽  
Multi Uav

This paper is concerned with relative localization-based optimal area coverage placement using multiple unmanned aerial vehicles (UAVs). It is assumed that only one of the UAVs has its global position information before performing the area coverage task and that ranging measurements can be obtained among the UAVs by using ultra-wide band (UWB) sensors. In this case, multi-UAV relative localization and cooperative coverage control have to be run simultaneously, which is a quite challenging task. In this paper, we propose a single-landmark-based relative localization algorithm, combined with a distributed coverage control law. At the same time, the optimal multi-UAV placement problem was formulated as a quadratic programming problem by compromising between optimal relative localization and optimal coverage control and was solved by using Sequential Quadratic Programming (SQP) algorithms. Simulation results show that our proposed method can guarantee that a team of UAVs can efficiently localize themselves in a cooperative manner and, at the same time, complete the area coverage task.

scholarly journals Distributed Formation Estimation Via Pairwise Distance Measurements

2021 ◽  
Vol 6 (2) ◽  
pp. 3017-3024
Author(s):  
Thomas Ziegler ◽  
Marco Karrer ◽  
Patrik Schmuck ◽  
Margarita Chli
Keyword(s):  
Pairwise Distance ◽  
Distance Measurements

A Research of Improving Data Fusing Algorithm Localization in Multistaic Sonar

2014 ◽  
Vol 530-531 ◽  
pp. 240-244
Author(s):  
Yong Sun ◽  
Jun Wei Zhao
Keyword(s):  
New Method ◽  
Localization Algorithm ◽  
Distance Measurements ◽  
Localization Accuracy ◽  
Sonar System ◽  
Measured Information ◽  
Simulation Results ◽  
Data Fusing

For the purpose of improving the localization accuracy of bistatic sonar in baseline districts and side districts, the most effective method is to increase the number of transmitting and receiving stations, which forms a multistatic sonar system. The mature algorithm of multistatic sonar system which contains three distance measurements volume in one subset, calls the multistatic time-only localization (TOL) algorithm. This paper proposes a new algorithm which merges the TOL algorithm and IBOL algorithm. of improving the bearing-only localization algorithm. The simulation results show that the proposed localization algorithm exhibits higher accuracy compared with the TOL algorithm and IBOL algorithm. This new method can take full application of the measured information to improved the localization accuracy in the whole controlled area.

scholarly journals Indoor pseudolite relative localization algorithm with kalman filter

2014 ◽  
Vol 63 (22) ◽  
pp. 228402
Author(s):  
Liu Yang-Yang ◽  
Lian Bao-Wang ◽  
Zhao Hong-Wei ◽  
Liu Ya-Qing
Keyword(s):  
Kalman Filter ◽  
Localization Algorithm ◽  
Relative Localization

INDOOR LOCALIZATION OF AN OMNI-DIRECTIONAL WHEELED MOBILE ROBOT

2013 ◽  
Vol 37 (4) ◽  
pp. 1043-1056 ◽  
Author(s):  
Sasha Ginzburg ◽  
Scott Nokleby
Keyword(s):  
Mobile Robot ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Wheeled Mobile Robot ◽  
Fusion Algorithm ◽  
Distance Measurements ◽  
Localization System ◽  
Relative Localization ◽  
Position And Orientation ◽  
Improved Performance

This paper presents a localization system developed for estimating the pose, i.e., position and orientation, of an omni-directional wheeled mobile robot operating in indoor structured environments. The developed system uses a combination of relative and absolute localization methods for pose estimation. Odometry serves as the relative localization method providing pose estimates through the integration of measurements obtained from shaft encoders on the robot’s drive motors. Absolute localization is achieved with a novel GPS-like system that performs localization of active beacons mounted on the mobile robot based on distance measurements to receivers fixed at known positions in the robot’s indoor workspace. A simple data fusion algorithm is used in the localization system to combine the pose estimates from the two localization methods and achieve improved performance. Experimental results demonstrating the performance of the developed system at localizing the omni-directional robot in an indoor environment are presented.

Implant Localization in Human Body Using Adaptive Least-Squares Based Algorithm

2013 ◽  
Author(s):  
Ahmet Çamlıca ◽  
Barış Fidan ◽  
Mustafa Yavuz
Keyword(s):  
Least Squares ◽  
Human Body ◽  
Estimation Error ◽  
Wide Band ◽  
Localization Algorithm ◽  
Convergence Properties ◽  
Forgetting Factor ◽  
Distance Measurements ◽  
Environmental Disturbances ◽  
Measurement Noises

In this study, we focus on the problem of localizing an implant or a capsule device in the human body by a mobile sensor unit using distance measurements. As a particular distance measurement technique, time of flight (TOF) based approach involving ultra wide-band signals is used, noting the important effects of the medium characteristics for different organs and tissue. We propose a least-squares based adaptive algorithm with forgetting factor to estimate the 3-D location of an implant in the human body. After discussing convergence properties of the proposed localization algorithm, we perform simulations to analyze the transient characteristics of the proposed algorithm. Different white Gaussian noises are added to emulate the TOF measurement noises and environmental disturbances, and it is observed that the proposed algorithm is robust to such noises/disturbances. The algorithm is successful in keeping the estimation error at a very low admissible level.

scholarly journals On Distributed Localization for Road Sensor Networks: A Game Theoretic Approach

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Jie Jia ◽  
Guiyuan Zhang ◽  
Xingwei Wang ◽  
Jian Chen
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Optimal Solution ◽  
Pairwise Distance ◽  
Potential Game ◽  
Theoretic Approach ◽  
Distance Measurements ◽  
Node Connectivity ◽  
Anchor Nodes ◽  
Game Theoretic

Road sensor network is an important part of vehicle networks system and is critical for many intelligent automobile scenarios, such as vehicle safety monitoring and transportation efficiency supporting. Localization of sensors is an active and crucial issue to most applications of road sensor network. Generally, given some anchor nodes’ positions and certain pairwise distance measurements, estimating the positions of all nonanchor nodes embodies a nonconvex optimization problem. However, due to the small number of anchor nodes and low sensor node connectivity degree in road sensor networks, the existing localization solutions are ineffective. In order to tackle this problem, a novel distributed localization method based on game theory for road sensor networks is proposed in this paper. Formally, we demonstrate that our proposed localization game is a potential game. Furthermore, we present several techniques to accelerate the convergence to the optimal solution. Simulation results demonstrate the effectiveness of our proposed algorithm.

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