scholarly journals Coverage Path Planning with Real-time Replanning and Surface Reconstruction for Inspection of Three-dimensional Underwater Structures using Autonomous Underwater Vehicles

2014 ◽  
Vol 32 (7) ◽  
pp. 952-983 ◽  
Author(s):  
Enric Galceran ◽  
Ricard Campos ◽  
Narcís Palomeras ◽  
David Ribas ◽  
Marc Carreras ◽  
...  
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Surface Reconstruction ◽  
Autonomous Underwater Vehicles ◽  
Three Dimensional ◽  
Underwater Vehicles ◽  
Coverage Path Planning ◽  
Underwater Structures

scholarly journals Profile Following for Inspection of Underwater Structures

2013 ◽  
Vol 4 (4) ◽  
Author(s):  
Enric Galceran ◽  
Narcís Palomeras ◽  
Marc Carreras
Keyword(s):  
Path Planning ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Target Structure ◽  
Coverage Path Planning ◽  
Bathymetric Data ◽  
Close Proximity ◽  
Profile Estimation ◽  
Probabilistic Map ◽  
Underwater Structures

AbstractWe present a seabed profile estimation and following method for close proximity inspection of 3D underwater structures using autonomous underwater vehicles (AUVs). The presented method is used to determine a path allowing the AUV to pass its sensors over all points of the target structure, which is known as coverage path planning. Our profile following method goes beyond traditional seabed following at a safe altitude and exploits hovering capabilities of recent AUV developments. A range sonar is used to incrementally construct a local probabilistic map representation of the environment and estimates of the local profile are obtained via linear regression. Two behavior-based controllers use these estimates to perform horizontal and vertical profile following. We build upon these tools to address coverage path planning for 3D underwater structures using a (potentially inaccurate) prior map and following cross-section profiles of the target structure. The feasibility of the proposed method is demonstrated using the GIRONA 500 AUV both in simulation using synthetic and real-world bathymetric data and in pool trials.

Three Dimensional Path Planning of Autonomous Underwater Vehicles

2013 ◽  
Vol 328 ◽  
pp. 128-132
Author(s):  
Yan Peng ◽  
Wei Qing Wu ◽  
Mei Liu ◽  
Shao Rong Xie ◽  
Jun Luo
Keyword(s):  
Lyapunov Function ◽  
Path Planning ◽  
Real Time ◽  
Tracking Control ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Three Dimensional ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Control Lyapunov Function

The path planning relates to the safe movement and navigation of the Autonomous Underwater Vehicles (AUV). This paper discusses the way of real-time path planning for autonomous underwater vehicle based on tracking control lyapunov function. The simulation conducted on H300 illustrates the effectiveness of proposed method.

An Algorithm of Complete Coverage Path Planning for Autonomous Underwater Vehicles

2011 ◽  
Vol 467-469 ◽  
pp. 1377-1385 ◽  
Author(s):  
Ming Zhong Yan ◽  
Da Qi Zhu
Keyword(s):  
Path Planning ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Time Varying ◽  
Simulation Studies ◽  
Complete Coverage ◽  
Biologically Inspired ◽  
Coverage Path Planning ◽  
Underwater Environment ◽  
Global Cost

Complete coverage path planning (CCPP) is an essential issue for Autonomous Underwater Vehicles’ (AUV) tasks, such as submarine search operations and complete coverage ocean explorations. A CCPP approach based on biologically inspired neural network is proposed for AUVs in the context of completely unknown environment. The AUV path is autonomously planned without any prior knowledge of the time-varying workspace, without explicitly optimizing any global cost functions, and without any learning procedures. The simulation studies show that the proposed approaches are capable of planning more reasonable collision-free complete coverage paths in unknown underwater environment.

A Method for Obtaining High-Coverage 3D Images of Rough Seafloor Using AUV – Real-Time Quality Evaluation and Path-Planning –

2013 ◽  
Vol 25 (2) ◽  
pp. 364-374 ◽  
Author(s):  
Ayaka Kume ◽  
◽  
Toshihiro Maki ◽  
Takashi Sakamaki ◽  
Tamaki Ura
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Quality Evaluation ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
New Method ◽  
3D Image ◽  
High Coverage ◽  
3D Images ◽  
Kagoshima Bay

Autonomous Underwater Vehicles (AUVs) are often used for seafloor exploration, and some AUVs are now being deployed to obtain detailed photomosaics of the seafloor. However, it is difficult for the results to be evaluated on-site, so the image maps obtained often have unscanned areas caused by occlusions, disturbances, etc. In order to improve the coverage of a map, operators have to plan a new path and then redeploy the AUV. This process is quite timeconsuming and troublesome. The authors propose a new method for an AUV to obtain a full-coverage 3D image of a rough, unknown seafloor in a single deployment. First, the AUV observes the seafloor by following a pre-determined path. Second, the AUV calculates the following on-site and based on the data obtained: 3D bathymetry map, unscanned areas on the map, and the next path that can be taken to image the unscanned areas effectively. Then, the AUV follows the new path to obtain better results. The performance of this proposed method is verified in both tank experiments and by simulation. In the experiments, the AUV “Tri-TON” succeeds in generating a route for a second observation, and the coverage increases from 73% to 82%. The performance of the method on the actual seafloor is verified using the results of the tank experiments and the bathymetry data on a chimney in Kagoshima Bay, Japan.

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.

Sign in / Sign up

Export Citation Format

Share Document