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 R-DFS: A Coverage Path Planning Approach Based on Region Optimal Decomposition

2021 ◽  
Vol 13 (8) ◽  
pp. 1525
Author(s):  
Gang Tang ◽  
Congqiang Tang ◽  
Hao Zhou ◽  
Christophe Claramunt ◽  
Shaoyang Men
Keyword(s):  
Path Planning ◽  
Google Earth ◽  
Simulation Experiments ◽  
Minimum Width ◽  
Coverage Path Planning ◽  
Optimal Paths ◽  
Planning Approach ◽  
Polygonal Area ◽  
Aerial Vehicle ◽  
Working Distance

Most Coverage Path Planning (CPP) strategies based on the minimum width of a concave polygonal area are very likely to generate non-optimal paths with many turns. This paper introduces a CPP method based on a Region Optimal Decomposition (ROD) that overcomes this limitation when applied to the path planning of an Unmanned Aerial Vehicle (UAV) in a port environment. The principle of the approach is to first apply a ROD to a Google Earth image of a port and combining the resulting sub-regions by an improved Depth-First-Search (DFS) algorithm. Finally, a genetic algorithm determines the traversal order of all sub-regions. The simulation experiments show that the combination of ROD and improved DFS algorithm can reduce the number of turns by 4.34%, increase the coverage rate by more than 10%, and shorten the non-working distance by about 29.91%. Overall, the whole approach provides a sound solution for the CPP and operations of UAVs in port environments.

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.

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

Complete Coverage Path Planning for Flexible Parent-Child Unit Robots

2015 ◽  
Author(s):  
Dare Olaonipekun ◽  
Joshua Vaughan
Keyword(s):  
Path Planning ◽  
Point Mass ◽  
Input Shaping ◽  
Flexible Robot ◽  
Complete Coverage ◽  
Coverage Path Planning ◽  
Coverage Process ◽  
Parent Child

This paper presents a complete coverage algorithm for a flexible parent child unit robot by combining input shaping with the wavefront algorithm. Input shaping was used to control the command-induced vibration in the system, while the wavefront algorithm planned the complete coverage path for a given workspace. A model of the flexible robot was developed by treating the child units as inputs, replacing the link wire by springs and dampers, and treating the parent unit as a point mass. Results showed significant improvement in the coverage process for the shaped coverage in comparison to the unshaped coverage.

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