scholarly journals MEMS IMU navigation with model based dead-reckoning and one-way-travel-time acoustic range measurements for autonomous underwater vehicles

2017 ◽  
Author(s):  
James Kepper
Keyword(s):  
Travel Time ◽  
Autonomous Underwater Vehicles ◽  
Dead Reckoning ◽  
Underwater Vehicles ◽  
Range Measurements ◽  
Model Based ◽  
Mems Imu

scholarly journals Communication Planning for Cooperative Terrain-Based Underwater Localization

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1675
Author(s):  
Jacob Anderson ◽  
Geoffrey A. Hollinger
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Dead Reckoning ◽  
Minimum Cost ◽  
Field Trials ◽  
Underwater Vehicles ◽  
Communication Policy ◽  
Time Step ◽  
Planning Algorithm ◽  
Communication Schedule ◽  
Communication Planning

This paper presents a decentralized communication planning algorithm for cooperative terrain-based navigation (dec-TBN) with autonomous underwater vehicles. The proposed algorithm uses forward simulation to approximate the value of communicating at each time step. The simulations are used to build a directed acyclic graph that can be searched to provide a minimum cost communication schedule. Simulations and field trials are used to validate the algorithm. The simulations use a real-world bathymetry map from Lake Nighthorse, CO, and a sensor model derived from an Ocean Server Iver2 vehicle. The simulation results show that the algorithm finds a communication schedule that reduces communication bandwidth by 86% and improves robot localization by up to 27% compared to non-cooperative terrain-based navigation. Field trials were conducted in Foster Reservoir, OR, using two Riptide Autonomous Solutions micro-unmanned underwater vehicles. The vehicles collected GPS, altimeter, acoustic communications, and dead reckoning data while following paths on the surface of the reservoir. The data were used to evaluate the planning algorithm. In three of four missions, the planning algorithm improved dec-TBN localization while reducing acoustic communication bandwidth by 56%. In the fourth mission, dec-TBN performed better when using full communications bandwidth, but the communication policy for that mission maintained 86% of the localization accuracy while using 9% of the communications. These results indicate that the presented communication planning algorithm can maintain or improve dec-TBN accuracy while reducing the number of communications used for localization.

Model-Based Maneuvering Controls for Autonomous Underwater Vehicles

1992 ◽  
Vol 114 (4) ◽  
pp. 614-622 ◽  
Author(s):  
A. J. Healey
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Reference Model ◽  
Autonomous Underwater Vehicles ◽  
Robustness Analysis ◽  
Underwater Vehicles ◽  
Feedback Systems ◽  
Model Based ◽  
Model Following Control ◽  
Handling Characteristics ◽  
Model Following

This paper proposes the development of a model following autopilot system for an Autonomous Underwater Vehicle (AUV) depth changing control. The parameters to command a maneuver are generated off-line and selected as appropriate by the vehicle’s autonomous control system. A series of such preprogrammed maneuvers can be stored in an on-board computer, and used as command generation systems for the autopilot. The paper presents a linear model following control (LMFC) design based on the open-loop linearized vehicle model as the reference model, a robustness analysis of the scheme and simulation results of response in the diveplane using the full nonlinear vehicle system equations. LMFC has been proposed for aircraft where certain desirable handling characteristics based on an arbitrary model are required or where decoupled control for Control Configured Vehicle (CCV) performance is needed. It is shown here that this model-based LMFC autopilot for underwater vehicles exhibits relatively robust behavior under conditions of parameter uncertainty and non-linearity which is not worse than the equivalent LQR/LTR for linear output feedback systems. Also, a tailored transient response is provided, conducive to near time optimal response.

scholarly journals A Single-Way Ranging Localization of AUVs Based on PSO of Outliers Elimination

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xinnan Fan ◽  
Zhongjian Wu ◽  
Jianjun Ni ◽  
Chengming Luo
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Time Of Arrival ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Simulation Experiments ◽  
Range Measurements ◽  
Acoustic Localization ◽  
Long Baseline ◽  
Key Factor

Localization of autonomous underwater vehicles (AUVs) is a very important and challenging task for the AUVs applications. In long baseline underwater acoustic localization networks, the accuracy of single-way range measurements is the key factor for the precision of localization of AUVs, whether it is based on the way of time of arrival (TOA), time difference of arrival (TDOA), or angle of arrival (AOA). The single-way range measurements do not depend on water quality and can be taken from long distances; however, there are some limitations which exist in these measurements, such as the disturbance of the unknown current velocity and the outliers caused by sensors and errors of algorithm. To deal with these problems, an AUV self-localization algorithm based on particle swarm optimization (PSO) of outliers elimination is proposed, which improves the performance of angle of arrival (AOA) localization algorithm by taking account of effects of the current on the positioning accuracy and eliminating possible outliers during the localization process. Some simulation experiments are carried out to illustrate the performance of the proposed method compared with another localization algorithm.

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