scholarly journals Hexagon-Based Generalized Voronoi Diagrams Generation for Path Planning of Intelligent Agents

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Fen Tang ◽  
Xiong You ◽  
Xin Zhang ◽  
Kunwei Li
Keyword(s):  
Path Planning ◽  
Computer Games ◽  
Intelligent Agents ◽  
Voronoi Diagrams ◽  
Simulation Experiments ◽  
Square Grid ◽  
Surrounding Environment ◽  
Hexagonal Grids ◽  
Generalized Voronoi Diagrams ◽  
Grid Based

Grid-based Generalized Voronoi Diagrams (GVDs) are widely used to represent the surrounding environment of intelligent agents in the fields of robotics, computer games, and military simulations, which improve the efficiency of path planning of intelligent agents. Current studies mainly focus on square-grid-based GVD construction approaches, and little attention has been paid to constructing GVDs from hexagonal grids. In this paper, an algorithm named hexagon-based crystal growth (HCG) is presented to extract GVDs from hexagonal grids. In addition, two thinning patterns for obtaining one-cell-wide GVDs from rough hexagon-based GVDs are proposed. On the basis of the principles of a leading square-grid-based algorithm named Brushfire, a hexagon-based Brushfire algorithm is realized. A comparison of the HCG and the hexagon-based Brushfire algorithm shows that HCG is much more efficient. Further, the usefulness of hexagon-based GVDs for the path planning tasks of intelligent agents is demonstrated using several representative simulation experiments.

scholarly journals Dynamic Detection of Topological Information from Grid-Based Generalized Voronoi Diagrams

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Long Qin ◽  
Quanjun Yin ◽  
Yabing Zha ◽  
Yong Peng
Keyword(s):  
Spatial Reasoning ◽  
Voronoi Diagrams ◽  
Dynamic Environments ◽  
Topological Information ◽  
Dynamic Topology ◽  
Order Of Magnitude ◽  
Generalized Voronoi Diagrams ◽  
High Level ◽  
Grid Based ◽  
Magnitude Improvement

In the context of robotics, the grid-based Generalized Voronoi Diagrams (GVDs) are widely used by mobile robots to represent their surrounding area. Current approaches for incrementally constructing GVDs mainly focus on providing metric skeletons of underlying grids, while the connectivity among GVD vertices and edges remains implicit, which makes high-level spatial reasoning tasks impractical. In this paper, we present an algorithm named Dynamic Topology Detector (DTD) for extracting a GVD with topological information from a grid map. Beyond the construction and reconstruction of a GVD on grids, DTD further extracts connectivity among the GVD edges and vertices. DTD also provides efficient repair mechanism to treat with local changes, making it work well in dynamic environments. Simulation tests in representative scenarios demonstrate that (1) compared with the static algorithms, DTD generally makes an order of magnitude improvement regarding computation times when working in dynamic environments; (2) with negligible extra computation, DTD detects topologies not computed by existing incremental algorithms. We also demonstrate the usefulness of the resulting topological information for high-level path planning tasks.

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.

Coverage Path Planning with Proximal Policy Optimization in a Grid-based Environment

2020 ◽  
Author(s):  
Aleksandr Ianenko ◽  
Alexander Artamonov ◽  
Georgii Sarapulov ◽  
Alexey Safaraleev ◽  
Sergey Bogomolov ◽  
...  
Keyword(s):  
Path Planning ◽  
Coverage Path Planning ◽  
Policy Optimization ◽  
Grid Based

scholarly journals Incremental Construction of Generalized Voronoi Diagrams on Pointerless Quadtrees

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Quanjun Yin ◽  
Long Qin ◽  
Xiaocheng Liu ◽  
Yabing Zha
Keyword(s):  
Voronoi Diagrams ◽  
Surrounding Area ◽  
Repair Mechanism ◽  
Local Repair ◽  
Order Of Magnitude ◽  
Generalized Voronoi Diagrams ◽  
Incremental Construction ◽  
Coarse To Fine ◽  
Multiple Granularities ◽  
Magnitude Improvement

In robotics, Generalized Voronoi Diagrams (GVDs) are widely used by mobile robots to represent the spatial topologies of their surrounding area. In this paper we consider the problem of constructing GVDs on discrete environments. Several algorithms that solve this problem exist in the literature, notably the Brushfire algorithm and its improved versions which possess local repair mechanism. However, when the area to be processed is very large or is of high resolution, the size of the metric matrices used by these algorithms to compute GVDs can be prohibitive. To address this issue, we propose an improvement on the current algorithms, using pointerless quadtrees in place of metric matrices to compute and maintain GVDs. Beyond the construction and reconstruction of a GVD, our algorithm further provides a method to approximate roadmaps in multiple granularities from the quadtree based GVD. Simulation tests in representative scenarios demonstrate that, compared with the current algorithms, our algorithm generally makes an order of magnitude improvement regarding memory cost when the area is larger than210×210. We also demonstrate the usefulness of the approximated roadmaps for coarse-to-fine pathfinding tasks.

scholarly journals Regarding Jump Point Search and Subgoal Graphs

2019 ◽  
Author(s):  
Daniel D. Harabor ◽  
Tansel Uras ◽  
Peter J. Stuckey ◽  
Sven Koenig
Keyword(s):  
Path Planning ◽  
State Of The Art ◽  
Jump Point ◽  
Point Search ◽  
Planning Technique ◽  
First Time ◽  
Grid Based

In this paper, we define Jump Point Graphs (JP), a preprocessing-based path-planning technique similar to Subgoal Graphs (SG). JP allows for the first time the combination of Jump Point Search style pruning in the context of abstraction-based speedup techniques, such as Contraction Hierarchies. We compare JP with SG and its variants and report new state-of-the-art results for grid-based pathfinding.

Estimation of geometrically necessary dislocation density from filtered EBSD data by a local linear adaptation of smoothing splines

2019 ◽  
Vol 52 (3) ◽  
pp. 548-563 ◽  
Author(s):  
Anthony Seret ◽  
Charbel Moussa ◽  
Marc Bernacki ◽  
Javier Signorelli ◽  
Nathalie Bozzolo
Keyword(s):  
Electron Backscatter Diffraction ◽  
Smoothing Splines ◽  
Data Sets ◽  
Square Grid ◽  
Orientation Gradient ◽  
Geometrically Necessary Dislocation ◽  
Ebsd Data ◽  
Local Linear ◽  
Density Values ◽  
Hexagonal Grids

An implementation of smoothing splines is proposed to reduce orientation noise in electron backscatter diffraction (EBSD) data, and subsequently estimate more accurate geometrically necessary dislocation (GND) densities. The local linear adaptation of smoothing splines (LLASS) filter has two advantages over classical implementations of smoothing splines: (1) it allows for an intuitive calibration of the fitting versus smoothing trade-off and (2) it can be applied directly and in the same manner to both square and hexagonal grids, and to 2D as well as to 3D EBSD data sets. Furthermore, the LLASS filter calculates the filtered orientation gradient, which is actually at the core of the method and which is subsequently used to calculate the GND density. The LLASS filter is applied on a simulated low-misorientation-angle boundary corrupted by artificial orientation noise (on a square grid), and on experimental EBSD data of a compressed Ni-base superalloy (acquired on a square grid) and of a dual austenitic/martensitic steel (acquired on an hexagonal grid). The LLASS filter leads to lower GND density values as compared to raw EBSD data sets, as a result of orientation noise being reduced, while preserving true GND structures. In addition, the results are compared with those of filters available in theMTEXtoolbox.

scholarly journals A Path-Planning Strategy for Unmanned Surface Vehicles Based on an Adaptive Hybrid Dynamic Stepsize and Target Attractive Force-RRT Algorithm

2019 ◽  
Vol 7 (5) ◽  
pp. 132 ◽  
Author(s):  
Zhen Zhang ◽  
Defeng Wu ◽  
Jiadong Gu ◽  
Fusheng Li
Keyword(s):  
Path Planning ◽  
High Speed ◽  
Attractive Force ◽  
Simulation Experiments ◽  
Planning Strategy ◽  
Unmanned Surface Vehicles ◽  
Planning Algorithm ◽  
Pass Through ◽  
Path Planning Algorithm ◽  
Narrow Area

It is well known that path planning has always been an important study area for intelligent ships, especially for unmanned surface vehicles (USVs). Therefore, it is necessary to study the path-planning algorithm for USVs. As one of the basic algorithms for USV path planning, the rapidly-exploring random tree (RRT) is popular due to its simple structure, high speed and ease of modification. However, it also has some obvious drawbacks and problems. Designed to perfect defects of the basic RRT and improve the performance of USVs, an enhanced algorithm of path planning is proposed in this study, called the adaptive hybrid dynamic stepsize and target attractive force-RRT(AHDSTAF-RRT). The ability to pass through a narrow area and the forward speed in open areas of USVs are improved by adopting the AHDSTAF-RRT in comparison to the basic RRT algorithm. The improved algorithm is also applied to an actual gulf map for simulation experiments, and the experimental data is collected and organized. Simulation experiments show that the proposed AHDSTAF-RRT in this paper outperforms several existing RRT algorithms, both in terms of path length and calculating speed.

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