scholarly journals Research on Path Planning Method of Coal Mine Robot to Avoid Obstacle in Gas Distribution Area

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Ruiqing Mao ◽  
Xiliang Ma
Keyword(s):  
Path Planning ◽  
Coal Mine ◽  
Ant Colony Algorithm ◽  
Planning Method ◽  
Working Environment ◽  
Distribution Area ◽  
Dijkstra Algorithm ◽  
Gas Distribution ◽  
Safety Level ◽  
Planning Methods

As the explosion-proof safety level of a coal mine robot has not yet reached the level of intrinsic safety “ia” and it cannot work in a dangerous gas distribution area, therefore, path planning methods for coal mine robot to avoid the dangerous area of gas are necessary. In this paper, to avoid a secondary explosion when the coal mine robot passes through gas hazard zones, a path planning method is proposed with consideration of gas concentration distributions. First, with consideration of gas distribution area and obstacles, MAKLINK method is adopted to describe the working environment network diagram of the coal mine robot. Second, the initial working paths for the coal mine robot are obtained based on Dijkstra algorithm, and then the global optimal working path for the coal mine robot is obtained based on ant colony algorithm. Lastly, experiments are conducted in a roadway after an accident, and results by different path planning methods are compared, which verified the effectiveness of the proposed path planning method.

scholarly journals Path planning for coal mine robot to avoid obstacle in gas distribution area

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141775150 ◽  
Author(s):  
Xiliang Ma ◽  
Ruiqing Mao
Keyword(s):  
Path Planning ◽  
Coal Mine ◽  
Ant Colony Algorithm ◽  
Dynamic Environment ◽  
Planning Method ◽  
Distribution Area ◽  
Dijkstra Algorithm ◽  
Safety Level ◽  
Planning Methods ◽  
Local Path

As the explosion-proof safety level of coal mine robot has not yet reached the level of intrinsic safety “ia,” therefore, path planning methods for coal mine robot to avoid the dangerous area of gas are necessary. To avoid a secondary explosion when the coal mine robot passes through gas hazard zones, a path planning method is proposed, considering the gas concentration distributions. The path planning method is composed of two steps in total: the global path planning and the local path adjustment. First, the global working path for coal mine robot is planed based on the Dijkstra algorithm and the ant colony algorithm. Second, with consideration of the dynamic environment, when hazardous gas areas distribute over the planed working path again, local path adjustments are carried out with the help of a proposed local path adjustment method. Lastly, experiments are conducted in a roadway after accident, which verify the effectiveness of the proposed path planning method.

A Review of Path Planning Method for Mobile Robot

2014 ◽  
Vol 1030-1032 ◽  
pp. 1588-1591 ◽  
Author(s):  
Zong Sheng Wu ◽  
Wei Ping Fu
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimal Path ◽  
Grid Method ◽  
Field Method ◽  
Planning Method ◽  
Artificial Potential Field ◽  
Planning Methods ◽  
Basic Ideas ◽  
Artificial Potential Field Method

The ability of a mobile robot to plan its path is the key task in the field of robotics, which is to find a shortest, collision free, optimal path in the various scenes. In this paper, different existing path planning methods are presented, and classified as: geometric construction method, artificial intelligent path planning method, grid method, and artificial potential field method. This paper briefly introduces the basic ideas of the four methods and compares them. Some challenging topics are presented based on the reviewed papers.

A path planning method using adaptive polymorphic ant colony algorithm for smart wheelchairs

2018 ◽  
Vol 25 ◽  
pp. 50-57 ◽  
Author(s):  
Zhuqing Jiao ◽  
Kai Ma ◽  
Yiling Rong ◽  
Peng Wang ◽  
Hongkai Zhang ◽  
...  
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Planning Method ◽  
Ant Colony ◽  
Smart Wheelchairs

scholarly journals An evaluation of path-planning methods for autonomous underwater vehicle based on terrain-aided navigation

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141985318
Author(s):  
Zheng Cong ◽  
Ye Li ◽  
Yanqing Jiang ◽  
Teng Ma ◽  
Yusen Gong ◽  
...  
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Positioning Accuracy ◽  
Planning Methods ◽  
Planning Algorithms ◽  
Motion Characteristics

This article presents a comparison of different path-planning algorithms for autonomous underwater vehicles using terrain-aided navigation. Four different path-planning methods are discussed: the genetic algorithm, the A* algorithm, the rapidly exploring random tree* algorithm, and the ant colony algorithm. The goal of this article is to compare the four methods to determine how to obtain better positioning accuracy when using terrain-aided navigation as a means of navigation. Each algorithm combines terrain complexity to comprehensively consider the motion characteristics of the autonomous underwater vehicles, giving reachable path between the start and end points. Terrain-aided navigation overcomes the challenges of underwater domain, such as visual distortion and radio frequency signal attenuation, which make landmark-based localization infeasible. The path-planning algorithms improve the terrain-aided navigation positioning accuracy by considering terrain complexity. To evaluate the four algorithms, we designed simulation experiments that use real-word seabed bathymetry data. The results of autonomous underwater vehicle navigation by terrain-aided navigation in these four cases are obtained and analyzed.

Obstacle Avoidance Path Planning for Harvesting Robot Manipulator Based on MAKLINK Graph and Improved Ant Colony Algorithm

2014 ◽  
Vol 530-531 ◽  
pp. 1063-1067 ◽  
Author(s):  
Wei Ji ◽  
Jun Le Li ◽  
De An Zhao ◽  
Yang Jun
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Ant Colony Algorithm ◽  
Robot Manipulator ◽  
Ant Colony ◽  
Dijkstra Algorithm ◽  
Short Time ◽  
Vector Description ◽  
Harvesting Robot ◽  
Improved Ant Colony Algorithm

To the problems of real-time obstacle avoidance path planning for apple harvesting robot manipulator in dynamic and unstructured environment, a method based on improved ant colony algorithm is presented. Firstly, Vector description is utilized to describe the area where obstacles such as branches is located as irregular polygon in free space, and MAKLINK graph is used to build up the environment space model. Then, the improved Dijkstra algorithm is used to find the initial walk path for apple harvesting robot manipulator. Finally, the improved ant colony algorithm is applied to optimize the initial path. The experiment result shows that the proposed method is simple and the robot manipulator can avoid the branches to pick the apple successfully in a relatively short time.

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