scholarly journals UAV Path Planning of Combining Ant Colony and Beetle Antennae Algorithm Using Intelligent Wireless Communication

2021 ◽  
Vol 2083 (2) ◽  
pp. 022058
Author(s):  
Le Xu ◽  
Wenlong Zhao
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Three Dimensional ◽  
Ant Colony ◽  
Fusion Algorithm ◽  
Third Order ◽  
Environment Model ◽  
Speed Up

Abstract In order to settle the problem of UAV path planning under mountain, an algorithm which based on the combination of ant colony algorithm and beetle antennae algorithm is proposed. Three dimensional environment model is established and objective function is constructed. It used ant colony algorithm to initialize the search path and the particle coordinates of all the next steps are updated by the beetle antennae algorithm. The improved algorithm adopted a new step update rule to speed up the convergence of the algorithm and used third-order B-spline interpolation method to smooth the path. Simulation results show that improved fusion algorithm has faster convergence speed and high stability by comparing with other algorithms under the same conditions, which verifies its effectiveness.

scholarly journals Fast Path Planning for On-Water Automatic Rescue Intelligent Robot Based on Constant Thrust Artificial Fluid Method

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yongqiang Qi ◽  
Yi Ke
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Interpolation Method ◽  
Three Dimensional ◽  
Intelligent Robot ◽  
Perturbation Matrix ◽  
Fluid Field ◽  
Environment Model ◽  
Simulation Results ◽  
Novel Algorithm

In this paper, fast path planning of on-water automatic rescue intelligent robot is studied based on the constant thrust artificial fluid method. First, a three-dimensional environment model is established, and then the kinematics equation of the robot is given. The constant thrust artificial fluid method based on the isochronous interpolation method is proposed, and a novel algorithm of constant thrust fitting is researched through the impulse compensation. The effect of obstacles on original fluid field is quantified by the perturbation matrix, and the streamlines can be regarded as the planned path. Simulation results demonstrate the effectiveness of this method by comparing with A-star algorithm and ant colony algorithm. It is proved that the planned path can avoid all obstacles smoothly and swiftly and reach the destination eventually.

Path Planning for the Chassis of Duct-Cleaning Robot Based on Ant Colony Algorithm

2012 ◽  
Vol 190-191 ◽  
pp. 715-718
Author(s):  
Qian Zhu ◽  
Wei Sun ◽  
Zhi Wei Zhou ◽  
Su Wei Zhang
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Optimal Path ◽  
Grid Method ◽  
Ant Colony ◽  
Simulation Experiments ◽  
Environment Model ◽  
Cleaning Robot ◽  
Duct Cleaning Robot ◽  
Duct Cleaning

For the path planning for the chassis of duct cleaning robot in an obstacle environment, ant colony algorithm and grid method are adopted to achieve an optimal path between two different arbitrary points and establish the environment model. The results of computer simulation experiments demonstrate the effectiveness of ant colony algorithm applied in path planning for the chassis of duct cleaning robot.

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.

Global Path Planning Method for USV System Based on Improved Ant Colony Algorithm

2014 ◽  
Vol 568-570 ◽  
pp. 785-788 ◽  
Author(s):  
Chang Hui Song
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Main Idea ◽  
Planning Method ◽  
Ant Colony ◽  
Grid Environment ◽  
Environment Model ◽  
Global Path Planning ◽  
The Right ◽  
Improved Ant Colony Algorithm

An improved ant colony algorithm based grid environment model for global path planning method for USV was introduced. The main idea of the improved ant colony algorithm was distributing each ant route dynamically. When the active ant was selecting the next route, this algorithm program determined the nearest direction to the end point. There were many possible route points which were distributed artificially. Thereby, the probability for each ant to choose the right direction was increased. The simulating results demonstrate that the improved ant colony algorithm in this paper is very suitable for solving the question of global path planning for USV system in the complex oceanic environment where there are a lot of obstacles. At the same time, this method costs less time, and the path is very smooth.

scholarly journals Path Planning Algorithm for Mobile Robot Based on Improved Ant Colony Algorithm

2021 ◽  
Vol 2083 (4) ◽  
pp. 042033
Author(s):  
Yanyun Li ◽  
Fenggang Liu
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Path Length ◽  
Ant Colony Algorithm ◽  
Planning Process ◽  
Optimal Path ◽  
Ant Colony ◽  
Position Information ◽  
Environment Model ◽  
Planning Algorithm

Abstract Due to the influence of full traversal environment, the path length obtained by existing methods is too long. In order to improve the performance of path planning and obtain the optimal path, a full traversal path planning method for omnidirectional mobile robots based on ant colony algorithm is proposed. On the basis of the topology modeling schematic diagram, according to the position information of the mobile robot in the original coordinate system, a new environment model is established by using the Angle transformation. Considering the existing problems of ant colony algorithm, the decline coefficient is introduced into the heuristic function to update the local pheromone, and the volatility coefficient of the pheromone is adjusted by setting the iteration threshold. Finally, through the design of path planning process, the planning of omnidirectional mobile robot’s full traversal path is realized. Experimental results show that the proposed method can not only shorten the full traversal path length, but also shorten the time of path planning to obtain the optimal path, thus improving the performance of full traversal path planning of omnidirectional mobile robot.

Research on path planning based on new fusion algorithm for autonomous vehicle

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142091123
Author(s):  
ChaoChun Yuan ◽  
Yue Wei ◽  
Jie Shen ◽  
Long Chen ◽  
Youguo He ◽  
...  
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Ant Colony Algorithm ◽  
Autonomous Vehicle ◽  
Ant Colony ◽  
Fusion Algorithm ◽  
Simulink Simulation ◽  
Initial Stage ◽  
Pheromone Concentration

Ant colony algorithm or artificial potential field is commonly used for path planning of autonomous vehicle. However, vehicle dynamics and road adhesion coefficient are not taken into consideration. In addition, ant colony algorithm has blindness/randomness due to low pheromone concentration at initial stage of obstacle avoidance path searching progress. In this article, a new fusion algorithm combining ant colony algorithm and improved potential field is introduced making autonomous vehicle avoid obstacle and drive more safely. Controller of path planning is modeled and analyzed based on simulation of CarSim and Simulink. Simulation results show that fusion algorithm reduces blindness at initial stage of obstacle avoidance path searching progress and verifies validity and efficiency of path planning. Moreover, all parameters of vehicle are changed within a reasonable range to meet requirements of steering stability and driving safely during path planning progress.

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