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.

scholarly journals Path Planning for Smart Car Based on Dijkstra Algorithm and Dynamic Window Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Li-sang Liu ◽  
Jia-feng Lin ◽  
Jin-xin Yao ◽  
Dong-wei He ◽  
Ji-shi Zheng ◽  
...  
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Autonomous Driving ◽  
Initial Position ◽  
Depth Information ◽  
Dijkstra Algorithm ◽  
Planning Algorithm ◽  
Local Path ◽  
Window Approach ◽  
Path Planning Algorithm

Path planning and obstacle avoidance are essential for autonomous driving cars. On the base of a self-constructed smart obstacle avoidance car, which used a LeTMC-520 depth camera and Jetson controller, this paper established a map of an unknown indoor environment based on depth information via SLAM technology. The Dijkstra algorithm is used as the global path planning algorithm and the dynamic window approach (DWA) as its local path planning algorithm, which are applied to the smart car, enabling it to successfully avoid obstacles from the planned initial position and reach the designated position. The tests on the smart car prove that the system can complete the functions of environment map establishment, path planning and navigation, and obstacle avoidance.

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.

scholarly journals Development of Path Planning Algorithm of Centipede Inspired Wheeled Robot in Presence of Static and Moving Obstacles Using ModifiedCritical-SnakeBug Algorithm

2019 ◽  
Vol 8 (2) ◽  
pp. 95
Author(s):  
Subir Kumar Das ◽  
Ajoy Kumar Dutta ◽  
Subir Kumar Debnath
Keyword(s):  
Path Planning ◽  
Real Life ◽  
Real Life Situation ◽  
Planning Algorithm ◽  
Dynamic Obstacle ◽  
Local Path ◽  
Stiff Body ◽  
Almost All ◽  
Path Planning Algorithm ◽  
Adaptation Ability

<p>Path planning for a movable robot in real life situation has been widely cultivated and become research interest for last few decades. Biomimetic robots have increased attraction for their capability to develop various kind of walking in order to navigate in different environment. To meet this requirement of natural insect locomotion has enabled the development of composite tiny robots. Almost all insect-scale legged robots take motivation from stiff-body hexapods; though, a different distinctive organism we find in nature is centipede, distinguished by its numerous legs and pliable body. This uniqueness is anticipated to present performance benefits to build robot of the said type in terms of swiftness, steadiness, toughness, and adaptation ability.</p>This paper proposes a local path planning algorithm of multiple rake centipede inspired robot namely ModifiedCritical-SnakeBug(MCSB) algorithm. Algorithm tries to avoid static and dynamic obstacle both. The results demonstrate the capability of the algorithm.

scholarly journals 2D Lidar-Based SLAM and Path Planning for Indoor Rescue Using Mobile Robots

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xuexi Zhang ◽  
Jiajun Lai ◽  
Dongliang Xu ◽  
Huaijun Li ◽  
Minyue Fu
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Basic System ◽  
Rescue Robot ◽  
Planning Algorithm ◽  
Local Path ◽  
Slam Algorithm ◽  
Path Planning Algorithm

As the basic system of the rescue robot, the SLAM system largely determines whether the rescue robot can complete the rescue mission. Although the current 2D Lidar-based SLAM algorithm, including its application in indoor rescue environment, has achieved much success, the evaluation of SLAM algorithms combined with path planning for indoor rescue has rarely been studied. This paper studies mapping and path planning for mobile robots in an indoor rescue environment. Combined with path planning algorithm, this paper analyzes the applicability of three SLAM algorithms (GMapping algorithm, Hector-SLAM algorithm, and Cartographer algorithm) in indoor rescue environment. Real-time path planning is studied to test the mapping results. To balance path optimality and obstacle avoidance, A ∗ algorithm is used for global path planning, and DWA algorithm is adopted for local path planning. Experimental results validate the SLAM and path planning algorithms in simulated, emulated, and competition rescue environments, respectively. Finally, the results of this paper may facilitate researchers quickly and clearly selecting appropriate algorithms to build SLAM systems according to their own demands.

A smooth local path planning algorithm based on modified visibility graph

2017 ◽  
Vol 31 (19-21) ◽  
pp. 1740091 ◽  
Author(s):  
Taizhi Lv ◽  
Maoyan Feng
Keyword(s):  
Path Planning ◽  
Simulation Experiment ◽  
Visibility Graph ◽  
Local Path Planning ◽  
Spline Curves ◽  
Smooth Path ◽  
Planning Algorithm ◽  
Path Search ◽  
Local Path ◽  
Path Planning Algorithm

Path planning is an essential and inevitable problem in robotics. Trapping in local minima and discontinuities often exist in local path planning. To overcome these drawbacks, this paper presents a smooth path planning algorithm based on modified visibility graph. This algorithm consists of three steps: (1) polygons are generated from detected obstacles; (2) a collision-free path is found by simultaneous visibility graph construction and path search by A[Formula: see text] (SVGA); (3) the path is smoothed by B-spline curves and particle swarm optimization (PSO). Simulation experiment results show the effectiveness of this algorithm, and a smooth path can be found fleetly.

scholarly journals NPQ-RRT ∗ : An Improved RRT ∗ Approach to Hybrid Path Planning

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zihan Yu ◽  
Linying Xiang
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Research Direction ◽  
Random Trees ◽  
Target Point ◽  
Evaluation Function ◽  
Local Planning ◽  
Planning Algorithm ◽  
Window Approach ◽  
Path Planning Algorithm

In recent years, the path planning of robot has been a hot research direction, and multirobot formation has practical application prospect in our life. This article proposes a hybrid path planning algorithm applied to robot formation. The improved Rapidly Exploring Random Trees algorithm PQ-RRT ∗ with new distance evaluation function is used as a global planning algorithm to generate the initial global path. The determined parent nodes and child nodes are used as the starting points and target points of the local planning algorithm, respectively. The dynamic window approach is used as the local planning algorithm to avoid dynamic obstacles. At the same time, the algorithm restricts the movement of robots inside the formation to avoid internal collisions. The local optimal path is selected by the evaluation function containing the possibility of formation collision. Therefore, multiple mobile robots can quickly and safely reach the global target point in a complex environment with dynamic and static obstacles through the hybrid path planning algorithm. Numerical simulations are given to verify the effectiveness and superiority of the proposed hybrid path planning algorithm.

AN EFFICIENT GRAPH THEORY-BASED ALGORITHM FOR SHIP TRAJECTORY PLANNING

2021 ◽  
Vol 161 (A2) ◽  
Author(s):  
A Lazarowska
Keyword(s):  
Graph Theory ◽  
Path Planning ◽  
Motion Control ◽  
Dynamic Environment ◽  
Computational Time ◽  
Optimization Approach ◽  
Application Area ◽  
A Algorithm ◽  
Planning Algorithm ◽  
Path Planning Algorithm

The research presented in this paper is dedicated to the development of a path planning algorithm for a moving object in a dynamic environment. The marine environment constitutes the application area. A graph theory-based path planning method for ships is introduced and supported by the results of simulation tests and comparative analysis with a heuristic Ant Colony Optimization approach. The method defines the environment with the use of a visibility graph and uses the A* algorithm to find the shortest, collision-free path. The main contribution is the development of an effective graph theory-based algorithm for path planning in an environment with static and dynamic obstacles. The computational time does not exceed a few seconds. Obtained results allow to state that the method is suitable for use in an intelligent motion control system for ships.

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