Real time visualisation of sensor data for an autonomous underwater vehicle via a Wi-Fi buoy

2012 ◽  
Author(s):  
Jeremy Breen ◽  
John McCulloch
Keyword(s):  
Real Time ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Sensor Data

scholarly journals Complete Coverage Path Planning in an Unknown Underwater Environment Based on D-S Data Fusion Real-Time Map Building

2012 ◽  
Vol 8 (10) ◽  
pp. 567959 ◽  
Author(s):  
Mingzhong Yan ◽  
Daqi Zhu ◽  
Simon X. Yang
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Autonomous Underwater Vehicle ◽  
Evidence Theory ◽  
Sensor Data ◽  
Map Building ◽  
Complete Coverage ◽  
Coverage Path Planning ◽  
Underwater Environment ◽  
Time Map

A real-time map-building system is proposed for an autonomous underwater vehicle (AUV) to build a map of an unknown underwater environment. The system, using the AUV's onboard sensor information, includes a neurodynamics model proposed for complete coverage path planning and an evidence theoretic method proposed for map building. The complete coverage of the environment guarantees that the AUV can acquire adequate environment information. The evidence theory is used to handle the noise and uncertainty of the sensor data. The AUV dynamically plans its path with obstacle avoidance through the landscape of neural activity. Concurrently, real-time sensor data are “fused” into a two-dimensional (2D) occupancy grid map of the environment using evidence inference rule based on the Dempster-Shafer theory. Simulation results show a good quality of map-building capabilities and path-planning behaviors of the AUV.

3D real-time tracking, following and imaging of white sharks with an Autonomous Underwater Vehicle

2015 ◽  
Author(s):  
Amy L. Kukulya ◽  
Roger Stokey ◽  
Robin Littlefield ◽  
Frederic Jaffre ◽  
Edgar Mauricio Hoyos Padilla ◽  
...  
Keyword(s):  
Real Time ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Real Time Tracking

scholarly journals An Overview of Autonomous Underwater Vehicle Research and Testbed at PeRL

2009 ◽  
Vol 43 (2) ◽  
pp. 33-47 ◽  
Author(s):  
Hunter C. Brown ◽  
Ayoung Kim ◽  
Ryan M. Eustice
Keyword(s):  
Real Time ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
University Of Michigan ◽  
Major Research ◽  
Research Areas ◽  
Localization And Mapping ◽  
Navigation And Control ◽  
The University ◽  
And Control

AbstractThis article provides a general overview of the autonomous underwater vehicle (AUV) research thrusts being pursued within the Perceptual Robotics Laboratory (PeRL) at the University of Michigan. Founded in 2007, PeRL's research centers on improving AUV autonomy via algorithmic advancements in environmentally based perceptual feedback for real-time mapping, navigation, and control. Our three major research areas are (1) real-time visual simultaneous localization and mapping (SLAM), (2) cooperative multi-vehicle navigation, and (3) perception-driven control. Pursuant to these research objectives, PeRL has developed a new multi-AUV SLAM testbed based upon a modified Ocean-Server Iver2 AUV platform. PeRL upgraded the vehicles with additional navigation and perceptual sensors for underwater SLAM research. In this article, we detail our testbed development, provide an overview of our major research thrusts, and put into context how our modified AUV testbed enables experimental real-world validation of these algorithms.

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