scholarly journals Global Path Planning for Unmanned Surface Vehicle Based on Improved Quantum Ant Colony Algorithm

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Guoqing Xia ◽  
Zhiwei Han ◽  
Bo Zhao ◽  
Caiyun Liu ◽  
Xinwei Wang
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
High Efficiency ◽  
Multiple Objectives ◽  
Ant Colony ◽  
Marine Environments ◽  
Global Path Planning ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Number Of Iterations

As a tool to monitor marine environments and to perform dangerous tasks instead of manned vessels, unmanned surface vehicles (USVs) have extensive applications. Because most path planning algorithms have difficulty meeting the mission requirements of USVs, the purpose of this study was to plan a global path with multiple objectives, such as path length, energy consumption, path smoothness, and path safety, for USV in marine environments. A global path planning algorithm based on an improved quantum ant colony algorithm (IQACA) is proposed. The improved quantum ant colony algorithm is an algorithm that benefits from the high efficiency of quantum computing and the optimization ability of the ant colony algorithm. The proposed algorithm can plan a path considering multiple objectives simultaneously. The simulation results show that the proposed algorithm’s obtained minimum was 2.1–6.5% lower than those of the quantum ant colony algorithm (QACA) and ant colony algorithm (ACA), and the number of iterations required to converge to the minimum was 11.2–24.5% lower than those of the QACA and ACA. In addition, the optimized path for the USV was obtained effectively and efficiently.

A Path-Planning Algorithm for AGV Based on the Combination between Ant Colony Algorithm and Immune Regulation

2011 ◽  
Vol 422 ◽  
pp. 3-9 ◽  
Author(s):  
Jian Zhong Huang ◽  
Yu Wan Cen
Keyword(s):  
Path Planning ◽  
Immune Regulation ◽  
Ant Colony Algorithm ◽  
Visibility Graph ◽  
Ant Colony ◽  
Environment Modeling ◽  
Environment Model ◽  
Global Path Planning ◽  
Planning Algorithm ◽  
Path Planning Algorithm

For the demand of AGV’s environment modeling and path-planning,the paper discusses how to establish static environment model of visibility graph and proposes a visibility table method.Moreover,based on the environment modeling,we put forward a new kind of global path-planning algorithm by the combination between ant colony algorithm and immune regulation.

The Mixing Algorithm of ACO and GA Based Global Path Planning Method for Mobile Robot

2014 ◽  
Vol 494-495 ◽  
pp. 1290-1293 ◽  
Author(s):  
Shi Gang Cui ◽  
Jiang Lei Dong ◽  
Fan Liang
Keyword(s):  
Path Planning ◽  
Distributed System ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Ant System ◽  
Global Path Planning ◽  
Planning Optimization ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Great Development

An ant colony algorithm is a stochastic searching optimization algorithm that is based on the heuristic behavior of the biologic colony. Its positive feedback and coordination make it possible to be applied to a distributed system. It has favorable adaptability in solving combinatorial optimization and has great development potential for its connotative parallel property. This study focused on global path planning with an ant colony algorithm in an environment based on grids, which explores a new path planning algorithm. How to present and update the pheromone of an ant system was investigated. The crossover operation of a genetic algorithm was used in the ant system for path optimization. Experimental results show that the algorithm has better path planning optimization ability than other algorithms.

scholarly journals Rapid global path planning algorithm for unmanned surface vehicles in large-scale and multi-island marine environments

2021 ◽  
Vol 7 ◽  
pp. e612
Author(s):  
Dong Wang ◽  
Jie Zhang ◽  
Jiucai Jin ◽  
Deqing Liu ◽  
Xingpeng Mao
Keyword(s):  
Path Planning ◽  
Large Scale ◽  
Distance Constraint ◽  
Marine Environments ◽  
Fast Marching ◽  
Unmanned Surface Vehicles ◽  
Grid Map ◽  
Global Path Planning ◽  
Planning Algorithm ◽  
Path Planning Algorithm

A global path planning algorithm for unmanned surface vehicles (USVs) with short time requirements in large-scale and complex multi-island marine environments is proposed. The fast marching method-based path planning for USVs is performed on grid maps, resulting in a decrease in computer efficiency for larger maps. This can be mitigated by improving the algorithm process. In the proposed algorithm, path planning is performed twice in maps with different spatial resolution (SR) grids. The first path planning is performed in a low SR grid map to determine effective regions, and the second is executed in a high SR grid map to rapidly acquire the final high precision global path. In each path planning process, a modified inshore-distance-constraint fast marching square (IDC-FM2) method is applied. Based on this method, the path portions around an obstacle can be constrained within a region determined by two inshore-distance parameters. The path planning results show that the proposed algorithm can generate smooth and safe global paths wherein the portions that bypass obstacles can be flexibly modified. Compared with the path planning based on the IDC-FM2 method applied to a single grid map, this algorithm can significantly improve the calculation efficiency while maintaining the precision of the planned path.

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