A Algorithm of Path Planning Based on Multiple Mobile Robots

2013 ◽  
Vol 470 ◽  
pp. 621-624 ◽  
Author(s):  
Xiao Dong Tan ◽  
Xu Wang ◽  
Pi Wei Song
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Dynamic Environment ◽  
Grid Method ◽  
Intelligent Robot ◽  
A Algorithm ◽  
Environmental Model ◽  
Multiple Mobile Robots ◽  
Traffic Rules

The environment of automated warehouse is complex. Path collision exists conflict between intelligent robot with unknown obstacles and intelligent mobile-robot, increasing the difficulty in multiple mobile robots path planning.To solve the problem, firstly working environmental model is established with traffic rules method and the grid method. Then the whole system adopts the idea of hierarchical cooperation for dynamic local and global path planning.By simulation this method is suitable for dynamic environment with known and unknown obstacles and effectively solve the problem of path planning for multiple mobile robots in automated warehouse.

scholarly journals Safe Path Planning of Mobile Robot in a known Dynamic Environment

2019 ◽  
Vol 9 (2) ◽  
pp. 2434-2439
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Real Time ◽  
Dynamic Environment ◽  
Mobile Robot Navigation ◽  
Matlab Simulation ◽  
A Algorithm ◽  
New Approach ◽  
Probability Of Collision ◽  
Safe Path

Path planning in mobile robot navigation is an advanced method of calculating the safe and obstacle free path in static and dynamic environments are involved between source point to destination. Real time path planning method defines that how a robot can make a decision when some unknown obstacle gets encountered in the path of navigation for a dynamic situation. At the point when an obstruction comes in the way of route, the robot must choose another and safe way to advance towards the objective by evading any impact. This study is focused on exploring the algorithm that gives the safe and shortest path when an obstacle changes the environment. By using A* algorithm in MATLAB simulation the probability of collision with obstacle and robot get increased. In this simulation work a new approach of path planning has been found by placing the virtual obstacles in the environment. A new obstacle get influence in the path of navigation, using virtual obstacle boundary around the new obstacle a short and safe path get evaluated which is collision free or low risk path . The purpose for this paper is to create a dependable and smooth direction in a real time domain with impediments and to manage the robot towards the target without hitting the obstacles also considering the size of the robot

scholarly journals Path Planning for Multiple Mobile Robots Using A* Algorithm

2017 ◽  
Vol 132 (3) ◽  
pp. 685-688 ◽  
Author(s):  
Z. Batik Garip ◽  
D. Karayel ◽  
S.S. Ozkan ◽  
G. Atali
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
A Algorithm ◽  
Multiple Mobile Robots

scholarly journals Research on path planning of three-neighbor search A* algorithm combined with artificial potential field

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110264
Author(s):  
Jiqing Chen ◽  
Chenzhi Tan ◽  
Rongxian Mo ◽  
Hongdu Zhang ◽  
Ganwei Cai ◽  
...  
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Path Length ◽  
Search Time ◽  
Experimental Results ◽  
Artificial Potential Field ◽  
A Algorithm ◽  
Neighbor Search

Among the shortcomings of the A* algorithm, for example, there are many search nodes in path planning, and the calculation time is long. This article proposes a three-neighbor search A* algorithm combined with artificial potential fields to optimize the path planning problem of mobile robots. The algorithm integrates and improves the partial artificial potential field and the A* algorithm to address irregular obstacles in the forward direction. The artificial potential field guides the mobile robot to move forward quickly. The A* algorithm of the three-neighbor search method performs accurate obstacle avoidance. The current pose vector of the mobile robot is constructed during obstacle avoidance, the search range is narrowed to less than three neighbors, and repeated searches are avoided. In the matrix laboratory environment, grid maps with different obstacle ratios are compared with the A* algorithm. The experimental results show that the proposed improved algorithm avoids concave obstacle traps and shortens the path length, thus reducing the search time and the number of search nodes. The average path length is shortened by 5.58%, the path search time is shortened by 77.05%, and the number of path nodes is reduced by 88.85%. The experimental results fully show that the improved A* algorithm is effective and feasible and can provide optimal results.

Path planning for mobile robots based on visibility graphs and A* algorithm

2015 ◽  
Author(s):  
Juan D. Contreras ◽  
Fernando Martínez S. ◽  
Fredy H. Martínez S.
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
A Algorithm ◽  
Visibility Graphs
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