Complete Coverage Path Planning of UUV for Marine Mine Countermeasure Using Grid Division and Spanning Tree

2019 ◽  
Author(s):  
Hongchuan Luo ◽  
Haifeng Lin ◽  
Tao Zhu ◽  
Zhao Kang
Keyword(s):  
Path Planning ◽  
Spanning Tree ◽  
Complete Coverage ◽  
Coverage Path Planning ◽  
Grid Division

scholarly journals Optimal Multirobot Coverage Path Planning: Ideal-Shaped Spanning Tree

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Chunqing Gao ◽  
Yingxin Kou ◽  
Zhanwu Li ◽  
An Xu ◽  
You Li ◽  
...  
Keyword(s):  
Path Planning ◽  
Spanning Tree ◽  
Spanning Trees ◽  
Optimal Path ◽  
Polynomial Algorithms ◽  
Minimum Length ◽  
Second Phase ◽  
Complete Coverage ◽  
Preparation Time ◽  
Coverage Path Planning

The present paper attempts to find the optimal coverage path for multiple robots in a given area including obstacles. For single robot coverage path planning (CPP) problem, an improved ant colony optimization (ACO) algorithm is proposed to construct the best spanning tree and then obtain the optimal path, which contributes to minimizing the energy/time consumption. For the multirobot case, first the DARP (Divide Areas based on Robots Initial Positions) algorithm is utilized to divide the area into separate equal subareas, so much so that it transforms the mCPP problem into several CPP problems, degrading the computation complexity. During the second phase, spanning tree in each subarea is constructed by the aforementioned algorithm. In the last phase, the specific end nodes are exchanged among subareas to achieve ideal-shaped spanning trees, which can also decrease the number of turns in coverage path. And the complete algorithms are proven to be approximately polynomial algorithms. Finally, the simulation confirms the complete algorithms’ advantages: complete coverage, nonbacktracks, minimum length, zero preparation time, and the least number of turns.

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.

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.

Complete coverage path planning for aerial vehicle flocks deployed in outdoor environments

2019 ◽  
Vol 75 ◽  
pp. 189-201 ◽  
Author(s):  
Dario Calogero Guastella ◽  
Luciano Cantelli ◽  
Giuseppe Giammello ◽  
Carmelo Donato Melita ◽  
Gianluca Spatino ◽  
...  
Keyword(s):  
Path Planning ◽  
Complete Coverage ◽  
Coverage Path Planning ◽  
Outdoor Environments ◽  
Aerial Vehicle

scholarly journals Complete Coverage Path Planning for a Multi-UAV Response System in Post-Earthquake Assessment

Robotics ◽  
2016 ◽  
Vol 5 (4) ◽  
pp. 26 ◽  
Author(s):  
Arman Nedjati ◽  
Gokhan Izbirak ◽  
Bela Vizvari ◽  
Jamal Arkat
Keyword(s):  
Path Planning ◽  
Complete Coverage ◽  
Coverage Path Planning ◽  
Response System ◽  
Earthquake Assessment ◽  
Multi Uav

Time-efficient and complete coverage path planning based on flow networks for multi-robots

2013 ◽  
Vol 11 (2) ◽  
pp. 369-376 ◽  
Author(s):  
Adiyabaatar Janchiv ◽  
Dugarjav Batsaikhan ◽  
ByungSoo Kim ◽  
Won Gu Lee ◽  
Soon-Geul Lee
Keyword(s):  
Path Planning ◽  
Flow Networks ◽  
Complete Coverage ◽  
Coverage Path Planning
Sign in / Sign up

Export Citation Format

Share Document