Research on pull-type multi-AGV system dynamic path optimization based on time window

2021 ◽  
pp. 095440702098271
Author(s):  
Hongying Shan ◽  
Chuang Wang ◽  
Cungang Zou ◽  
Mengyao Qin
Keyword(s):  
Path Planning ◽  
Time Window ◽  
Planning Problem ◽  
Dijkstra Algorithm ◽  
Before And After ◽  
Common Planning ◽  
Planning Algorithm ◽  
Dynamic Path ◽  
Set Up ◽  
Path Planning Algorithm

This paper is a study of the dynamic path planning problem of the pull-type multiple Automated Guided Vehicle (multi-AGV) complex system. First, based on research status at home and abroad, the conflict types, common planning algorithms, and task scheduling methods of different AGV complex systems are compared and analyzed. After comparing the different algorithms, the Dijkstra algorithm was selected as the path planning algorithm. Secondly, a mathematical model is set up for the shortest path of the total driving path, and a general algorithm for multi-AGV collision-free path planning based on a time window is proposed. After a thorough study of the shortcomings of traditional single-car planning and conflict resolution algorithms, a time window improvement algorithm for the planning path and the solution of the path conflict covariance is established. Experiments on VC++ software showed that the improved algorithm reduces the time of path planning and improves the punctual delivery rate of tasks. Finally, the algorithm is applied to material distribution in the OSIS workshop of a C enterprise company. It can be determined that the method is feasible in the actual production and has a certain application value by the improvement of the data before and after the comparison.

Dynamic Path Planning Algorithm Based on Chaos Genetic Vehicle Navigation

2011 ◽  
Vol 142 ◽  
pp. 12-15
Author(s):  
Ping Feng
Keyword(s):  
Path Planning ◽  
Search Algorithm ◽  
Traffic Condition ◽  
Planning Time ◽  
Dynamic Path Planning ◽  
Short Period ◽  
Planning Algorithm ◽  
Dynamic Path ◽  
Path Planning Algorithm ◽  
Chaos Genetic Algorithm

The paper puts forward the dynamic path planning algorithm based on improving chaos genetic algorithm by using genetic algorithms and chaos search algorithm. In the practice of navigation, the algorithm can compute at the best path to meet the needs of the navigation in such a short period of planning time. Furthermore,this algorithm can replan a optimum path of the rest paths after the traffic condition in the sudden.

Collision-Free Motion Planning for an Aligned Multiple-turret System Operating in Extreme Environment

Robotica ◽  
2021 ◽  
pp. 1-30
Author(s):  
Ümit Yerlikaya ◽  
R.Tuna Balkan
Keyword(s):  
Path Planning ◽  
Extreme Environment ◽  
Configuration Spaces ◽  
Planning Problem ◽  
Different Types ◽  
Planning Algorithm ◽  
Line Path ◽  
Path Planning Algorithm ◽  
Path Planning Problem ◽  
System Operating

Abstract Instead of using the tedious process of manual positioning, an off-line path planning algorithm has been developed for military turrets to improve their accuracy and efficiency. In the scope of this research, an algorithm is proposed to search a path in three different types of configuration spaces which are rectangular-, circular-, and torus-shaped by providing three converging options named as fast, medium, and optimum depending on the application. With the help of the proposed algorithm, 4-dimensional (D) path planning problem was realized as 2-D + 2-D by using six sequences and their options. The results obtained were simulated and no collision was observed between any bodies in these three options.

Adaptive Dynamic Path Planning Algorithm for Interception of a Moving Target

2013 ◽  
Vol 5 (3) ◽  
pp. 19-33
Author(s):  
H. H. Triharminto ◽  
A.S. Prabuwono ◽  
T. B. Adji ◽  
N. A. Setiawan
Keyword(s):  
Path Planning ◽  
Dynamic Condition ◽  
Cylindrical Shape ◽  
Moving Target ◽  
C Language ◽  
Dynamic Path Planning ◽  
Planning Algorithm ◽  
Aerial Vehicle ◽  
Dynamic Path ◽  
Path Planning Algorithm

Most of the 3D curve path planning is used to build static path planning. For intercepting of a moving target, the path planning has to be set in a dynamic condition. L+Dumo algorithm which is based on curve is used to intercept a moving target. In the real situations, the Unmanned Aerial Vehicle (UAV) has possibility to intercept a moving target from all direction. It is assumed that environment of the UAV is in 3D Euclidean Space. It means that the UAV has to adapt for all quadrants for interception of a moving target. This research develops a path planning algorithm which enhances the previous L+Dumo algorithm to encounter the possibility quadrants. The enhancement would be simulated in C++ language to determine the accuracy of the algorithm. The simulation is conducted using one UAV and one moving target with random obstacles of cylindrical shape in between both objects. The result shows that the system accuracy is 81.0876%, a level which is able to encounter all possibility quadrants.

scholarly journals A Bi-Level Path Planning Algorithm for Multi-AGV Routing Problem

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1351
Author(s):  
Zhiheng Yuan ◽  
Zhengmao Yang ◽  
Lingling Lv ◽  
Yanjun Shi
Keyword(s):  
Path Planning ◽  
Random Trees ◽  
Dijkstra Algorithm ◽  
A Algorithm ◽  
Routing Problem ◽  
Agv Routing ◽  
Planning Algorithm ◽  
Local Grid ◽  
Local Path ◽  
Path Planning Algorithm

Avoiding the multi-automated guided vehicle (AGV) path conflicts is of importance for the efficiency of the AGV system, and we propose a bi-level path planning algorithm to optimize the routing of multi-AGVs. In the first level, we propose an improved A* algorithm to plan the AGV global path in the global topology map, which aims to make the path shortest and reduce the AGV path conflicts as much as possible. In the second level, we present the dynamic rapidly-exploring random trees (RRT) algorithm with kinematic constraints to obtain the passable local path with collisions in the local grid map. Compared to the Dijkstra algorithm and classic A* algorithm, the simulation results showed that the proposed bi-level path planning algorithm performed well in terms of the search efficiency, significantly reducing the incidence of multiple AGV path conflicts.

A genetic path planning algorithm for redundant articulated robots

Robotica ◽  
1997 ◽  
Vol 15 (2) ◽  
pp. 213-224 ◽  
Author(s):  
Andreas C. Nearchou ◽  
Nikos A. Aspragathos
Keyword(s):  
Path Planning ◽  
Degrees Of Freedom ◽  
Target Location ◽  
Planning Problem ◽  
Worst Case ◽  
Pick And Place ◽  
Planning Algorithm ◽  
A New Technique ◽  
Articulated Robots ◽  
Path Planning Algorithm

In some daily tasks, such as pick and place, the robot is requested to reach with its hand tip a desired target location while it is operating in its environment. Such tasks become more complex in environments cluttered with obstacles, since the constraint for collision-free movement must be also taken into account. This paper presents a new technique based on genetic algorithms (GAs) to solve the path planning problem of articulated redundant robot manipulators. The efficiency of the proposed GA is demonstrated through multiple experiments carried out on several robots with redundant degrees-of-freedom. Finally, the computational complexity of the proposed solution is estimated, in the worst case.

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