scholarly journals HAS4: A Heuristic Adaptive Sink Sensor Set Selection for Underwater AUV-Aid Data Gathering Algorithm

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4110 ◽  
Author(s):  
Xingwang Wang ◽  
Debing Wei ◽  
Xiaohui Wei ◽  
Junhong Cui ◽  
Miao Pan
Keyword(s):  
Cost Reduction ◽  
High Speed ◽  
Autonomous Underwater Vehicles ◽  
Data Gathering ◽  
Underwater Vehicles ◽  
Sensor Nodes ◽  
Selection Methods ◽  
Selection Algorithm ◽  
Underwater Wireless Sensor Networks ◽  
Selection For

In this paper, we target solving the data gathering problem in underwater wireless sensor networks. In many underwater applications, it is not quick to retrieve sensed data, which gives us the opportunity to leverage mobile autonomous underwater vehicles (AUV) as data mules to periodically collect it. For each round of data gathering, the AUV visits part of the sensors, and the communication between AUV and sensor nodes is a novel high-speed magnetic-induction communication system. The rest of the sensors acoustically transmit their sensed data to the AUV-visit sensors. This paper deploys the HAS 4 (Heuristic Adaptive Sink Sensor Set Selection) algorithm to select the AUV-visited sensors for the purpose of energy saving, AUV cost reduction and network lifetime prolonging. By comparing HAS 4 with two benchmark selection methods, experiment results demonstrate that our algorithm can achieve a better performance.

A Novel Classified Self-Organising Map Applied to Task Assignment

2020 ◽  
Vol 73 (5) ◽  
pp. 1129-1145
Author(s):  
Yun Qu ◽  
Daqi Zhu
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Task Assignment ◽  
Underwater Vehicles ◽  
The Self ◽  
Sensor Nodes ◽  
Sensor Technology ◽  
The Novel ◽  
Total Energy Consumption ◽  
Map Algorithm ◽  
Self Organising Map

With the development of sensor technology, sensor nodes are increasingly being used in underwater environments. The strategy presented in this paper is designed to solve the problem of using a limited number of autonomous underwater vehicles (AUVs) to complete tasks such as data collection from sensor nodes when the number of AUVs is less than the number of target sensors. A novel classified self-organising map algorithm is proposed to solve the problem. First, according to the K-means algorithm, targets are classified into groups that are determined by the number of AUVs. Second, according to the self-organising map algorithm, AUVs are matched with groups. Third, each AUV is provided with the accessible order of the targets in the group. The novel classified self-organising map algorithm can be used not only to reduce the total energy consumption in a multi-AUV system, but also to give the most efficient accessible order of targets for AUVs. Results of simulations conducted to prove the applicability of the algorithm are given.

scholarly journals Modeling and Control of Negative-Buoyancy Tri-Tilt-Rotor Autonomous Underwater Vehicles Based on Immersion and Invariance Methodology

2018 ◽  
Vol 8 (7) ◽  
pp. 1150 ◽  
Author(s):  
Tao Wang ◽  
Chao Wu ◽  
Jianqin Wang ◽  
Tong Ge
Keyword(s):  
High Speed ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Error Model ◽  
Nonlinear Controller ◽  
Tilt Rotor ◽  
Immersion And Invariance ◽  
Attitude Error ◽  
Negative Buoyancy

Spot hover and high speed capabilities of underwater vehicles are essential for ocean exploring, however, few vehicles have these two features. Moreover, the motion of underwater vehicles is prone to be affected by the unknown hydrodynamics. This paper presents a novel negative-buoyancy autonomous underwater vehicle equipped with tri-tilt-rotor to obtain these two features. A detailed mathematical model is derived, which is then decoupled to altitude and attitude subsystems. For controlling the underwater vehicle, an attitude error model is designed for the attitude subsystem, and an adaptive nonlinear controller is proposed for the attitude error model based on immersion and invariance methodology. To demonstrate the effectiveness of the proposed controller, a three degrees of freedom (DOF) testbed is developed, and the performance of the controller is validated through a real-time experiment.

scholarly journals Value of Information Based Data Retrieval in UWSNs

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3414 ◽  
Author(s):  
Fahad Khan ◽  
Sehar Butt ◽  
Saad Khan ◽  
Ladislau Bölöni ◽  
Damla Turgut
Keyword(s):  
Value Of Information ◽  
Autonomous Underwater Vehicle ◽  
Data Transfer ◽  
Autonomous Underwater Vehicles ◽  
Data Retrieval ◽  
Underwater Vehicles ◽  
Sensor Nodes ◽  
Underwater Sensor Networks ◽  
Optical Channels ◽  
Underwater Acoustic Channels

Sensor nodes in underwater sensor networks may acquire data at a higher rate than their ability to communicate over underwater acoustic channels. Autonomous underwater vehicles may mitigate this mismatch by offloading high volumes of data from the sensor nodes and ferrying them to the sink. Such a mode of data transfer results in high latency. Occasionally, these networks need to report high priority events such as catastrophes or intrusions. In such a scenario the expectation is to have a minimal end-to-end delay for event reporting. Considering this, underwater vehicles should schedule their visits to the sensor nodes in a manner that aids efficient reporting of high-priority events. We propose the use of the Value of Information metric in order to improve the reporting of events in an underwater sensor network. The proposed approach classifies the recorded data in terms of its value and priority. The classified data is transmitted using a combination of acoustic and optical channels. We perform experiments with a binary event model, i.e., we classify the events into high-priority and low-priority events. We explore a couple of different path planning strategies for the autonomous underwater vehicle. Our results show that scheduling visits to sensor nodes, based on algorithms that address the value of information, improves the timely reporting of high priority data and enables the accumulation of larger value of information.

A method for autonomous collision-free navigation of a quadrotor UAV in unknown tunnel-like environments

Robotica ◽  
2021 ◽  
pp. 1-27
Author(s):  
Taha Elmokadem ◽  
Andrey V. Savkin
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Autonomous Underwater Vehicles ◽  
Three Dimensional ◽  
Underwater Vehicles ◽  
Practical Implementation ◽  
Challenging Problem ◽  
Quadrotor Uav ◽  
Navigation Algorithm ◽  
Aerial Vehicles ◽  
Quadrotor Uavs

Abstract Unmanned aerial vehicles (UAVs) have become essential tools for exploring, mapping and inspection of unknown three-dimensional (3D) tunnel-like environments which is a very challenging problem. A computationally light navigation algorithm is developed in this paper for quadrotor UAVs to autonomously guide the vehicle through such environments. It uses sensors observations to safely guide the UAV along the tunnel axis while avoiding collisions with its walls. The approach is evaluated using several computer simulations with realistic sensing models and practical implementation with a quadrotor UAV. The proposed method is also applicable to other UAV types and autonomous underwater vehicles.

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