scholarly journals Path Planning in Multi-AGVs Using a Modified A-star Algorithm

2020 ◽  
Vol 8 (5) ◽  
pp. 273-282
Author(s):  
Xing Xu ◽  
Munashe Zhoya
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Traffic Congestion ◽  
New Technologies ◽  
Grid Method ◽  
Planning Problem ◽  
Automatic Guided Vehicles ◽  
Wide Scale ◽  
Waiting Strategy ◽  
Sorting System

The problem of path planning is a hot and exclusive research topic on multiple Automatic Guided Vehicles (multi-AGVs) systems. Many research results have been reported, but outrightly solving path planning problem from the perspective of reducing traffic congestion have faced obstacles. A collision-free path planning procedure based on a modified A-star Algorithm for multi-AGVs logistics sorting system is proposed in this paper. AGVs are now a poplar way to handle materials in latest smart warehouses. Many researches have been conducted and new technologies are still being developed. There is wide scale research on algorithms to help in scheduling, routing and path planning. Multi-AGVs are used to load goods automatically in a packaging factory. To ensure an effective and safe collision free path planning, this work investigates movement, scheduling and routing, speed manipulation and efficiency of machinery to target positions. The A-star algorithm with grid method to map out a typical warehouse scenario into multiple nodes was used. To have the shortest possible path, for obstacle avoidance, we employed the Braitenberg model. The waiting strategy is used for conflict resolution at intersections.

Path Planning for Spheres in Three Dimensional Environments With Low Interference Index

1994 ◽  
Author(s):  
Duane W. Storti ◽  
Debasish Dutta
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Configuration Space ◽  
Local Knowledge ◽  
Three Dimensional ◽  
Target Point ◽  
Planning Problem ◽  
Spherical Object ◽  
Starting Point ◽  
Path Planning Problem

Abstract We consider the path planning problem for a spherical object moving through a three-dimensional environment composed of spherical obstacles. Given a starting point and a terminal or target point, we wish to determine a collision free path from start to target for the moving sphere. We define an interference index to count the number of configuration space obstacles whose surfaces interfere simultaneously. In this paper, we present algorithms for navigating the sphere when the interference index is ≤ 2. While a global calculation is necessary to characterize the environment as a whole, only local knowledge is needed for path construction.

Path planning for intelligent robot based on switching local evolutionary PSO algorithm

2016 ◽  
Vol 36 (2) ◽  
pp. 120-126 ◽  
Author(s):  
Nianyin Zeng ◽  
Hong Zhang ◽  
Yanping Chen ◽  
Binqiang Chen ◽  
Yurong Liu
Keyword(s):  
Markov Chain ◽  
Path Planning ◽  
Three Dimensional ◽  
Grid Method ◽  
Pso Algorithm ◽  
Planning Problem ◽  
Homogeneous Markov Chain ◽  
Intelligent Robot ◽  
Environment Modeling ◽  
Content Type

Purpose This paper aims to present a novel particle swarm optimization (PSO) based on a non-homogeneous Markov chain and differential evolution (DE) for path planning of intelligent robot when having obstacles in the environment. Design/methodology/approach The three-dimensional path surface of the intelligent robot is decomposed into a two-dimensional plane and the height information in z axis. Then, the grid method is exploited for the environment modeling problem. After that, a recently proposed switching local evolutionary PSO (SLEPSO) based on non-homogeneous Markov chain and DE is analyzed for the path planning problem. The velocity updating equation of the presented SLEPSO algorithm jumps from one mode to another based on the non-homogeneous Markov chain, which can overcome the contradiction between local and global search. In addition, DE mutation and crossover operations can enhance the capability of finding a better global best particle in the PSO method. Findings Finally, the SLEPSO algorithm is successfully applied to the path planning in two different environments. Comparing with some well-known PSO algorithms, the experiment results show the feasibility and effectiveness of the presented method. Originality/value Therefore, this can provide a new method for the area of path planning of intelligent robot.

A Collision-Free Path Planning Method for an Articulated Mobile Robot in a Free Environment

2005 ◽  
Author(s):  
Patricia Quintero-Alvarez ◽  
Gabriel Ramirez ◽  
Sai¨d Zeghloul
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Free Path ◽  
Velocity Space ◽  
Control Law ◽  
Planning Problem ◽  
Optimization Approach ◽  
Reference Velocity ◽  
Free Environment ◽  
Path Planning Problem

In our previous work, we have treated the collision-free path-planning problem for a nonholonomic mobile robot in a cluttered environment. The method we have used is based on a representation of the obstacles in the robot’s velocity space, called Feasible Velocities Polygon (FVP). Every obstacle in the robot’s influence zone is represented by a linear constraint over the robot’s velocities such that it could not be collision between the robot and the obstacle. These constraints define a convex subset in the velocity space, the FVP. Every velocity vector of the FVP ensures a safe motion for the given obstacle configuration. The path-planning problem is solved by an optimization approach between the FVP and a reference velocity to reach the goal. In this paper, we have extended our work to an articulated mobile robot. This robot is composed of a differential mobile robot as tractor and a trailer, linked by off-center joints. We have modified the reference velocity in order to consider the constraints imposed by the trailer over the robot’s velocities. The control law is a nonlinear control law, which is asymptotically stable to the goal. We use the virtual robot concept, to solve the stability problem when the robot and its trailer move backwards. An articulated mobile robot is a strongly constrained system. Even in a free environment, under some circumstances, the robot may get blocked by its trailer in its progression towards the goal. To solve these situations, we have developed a heuristic algorithm. This algorithm is based in human experience: when a blocking situation is detected, a forward-backward maneuver is made, in order to increase the distance between the tows until a maximal value. After this maneuver, the robot takes the path to the original goal. Some numerical results show that our method leads the robot and the trailer to the final position in a stable way.

An approach to time-optimal, smooth and collision-free path planning in a two robot arm environment

Robotica ◽  
1996 ◽  
Vol 14 (1) ◽  
pp. 61-70 ◽  
Author(s):  
Bailin Cao ◽  
Gordon I. Dodds ◽  
George W. Irwin
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Industrial Robot ◽  
Planning Problem ◽  
Robot Arm ◽  
Rates Of Change ◽  
Time Optimal ◽  
Time Optimality ◽  
Path Planning Problem ◽  
Effective Collision

SummaryAn approach to time-optimal smooth and collision-free path planning for two industrial robot arms is presented, where path planning and joint trajectory generation are integrated. A suitable objective function, combining the requirements of time optimality and path smoothness, is proposed, which is subject to the continuity of joint trajectories, limits on their rates of change and collision-free constraints. Fast and effective collision detection for the arms is achieved using the Kuhn- Tucker conditions along with the convexity of the distance function and relying on geometrical relationships between cylinders. Nonlinear optimization is used to solve this path planning problem. The feasibility of this method is illustrated both by simulation and by experimental results.

scholarly journals A Collision-Free Path-Planning Method for an Articulated Mobile Robot

2007 ◽  
Vol 4 (2) ◽  
pp. 71-81 ◽  
Author(s):  
P. Quintero-Alvarez ◽  
G. Ramirez ◽  
S. Zeghloul
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Free Path ◽  
Planning Problem ◽  
Minimal Distance ◽  
Final Position ◽  
Cluttered Environment ◽  
Distance Calculation ◽  
Articulated Robot ◽  
Path Planning Problem

In previous works, we treated the collision-free path-planning problem for a nonholonomic mobile robot in a cluttered environment. We used a method based on a representation of the obstacles on the robot's velocity space. This representation is called Feasible Velocities Polygon (FVP). Every obstacle in the robot's influence zone is represented by a linear constraint on the robot's velocities such that a collision between the robot and the obstacle could be avoided. These constraints define a convex subset in the velocity space, the FVP. Every velocity vector in the FVP ensures a safe motion for the given obstacle configuration. The path-planning problem is solved by an optimization approach between the FVP and a reference velocity to reach the goal. In this paper, we have extended our work to an articulated mobile robot evolving in a cluttered environment. This robot is composed of a differential mobile robot and one or several modules that together form the trailer which are linked by off-center joints. This kind of robot is a strongly constrained system. Even in a free environment, under some circumstances, the robot may be blocked by its trailers in its progression towards the goal. The proposed approach, compared to other methods, has the main advantage of integrating anti-collision constraints between the articulated robot itself and the environment, in order to avoid and resolve dead-lock situations. For moving to the final position, the articulated mobile robot uses the FVP and a reference control law, to formulate the constraints method as a problem of minimal distance calculation. This formulation is then solved with the algorithm of minimal distance calculation proposed by Zeghloul (Zeghloul and Rambeaud, 1996). When a dead-locking situation arises and according to the robot–obstacle configuration, we have developed three different modules to solve these conditions. Each module uses a different approach to resolve the blocking situation. In order to show the capabilities of our method to lead the articulated robot to the final position in a stable way, a numerical result is presented.

scholarly journals Automatic Parking Path Planning Based on Ant Colony Optimization and the Grid Method

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Guo Liang Han
Keyword(s):  
Path Planning ◽  
Ant Colony Optimization ◽  
Shortest Path ◽  
Grid Method ◽  
Path Tracking ◽  
Planning Method ◽  
Ant Colony ◽  
Planning Problem ◽  
Automatic Parking ◽  
Vehicle Path

This paper analyzes the path planning problem in the automatic parking process, and studies a path planning method for automatic parking. The grid method and the ant colony optimization are combined to find the shortest path from the parking start point to the end point. The grid method is used to model the parking environment to simulate the actual parking space of automatic parking; then this paper makes some improvements to the basic ant colony optimization, finds the destination by setting the ants’ movement rules in the grid, and finds the shortest path after N iterations; since the optimal path found is a polyline, it will increase the difficulty of controlling vehicle path tracking and affect the accuracy of vehicle path tracking. The bezier curve is used to generate a smooth path suitable for vehicle walking. Finally, through matlab simulation, the obstacles in the environment are simulated, and the parking trajectory is obtained. The results show that the path planning method proposed in this paper is feasible.

Robot Path Planning Based on Artificial Fish Swarm Algorithm under a Known Environment

2014 ◽  
Vol 989-994 ◽  
pp. 2467-2469 ◽  
Author(s):  
Jian Wang ◽  
Li Juan Wu
Keyword(s):  
Path Planning ◽  
Grid Method ◽  
Planning Problem ◽  
Artificial Fish Swarm Algorithm ◽  
Starting Point ◽  
Swarm Behavior ◽  
Random Grid ◽  
Artificial Fish Swarm ◽  
Scope Of Application ◽  
Robot Path

With the development of science, the scope of application of robot is more and more extensive. The path planning problem of mobile robot ,has been always an important research content of intelligent robot .In this paper , firstly we can construct feasible work space mode , through the random grid method to given the starting point ,end point and each obstacle .Then we can use the improved AFSA for path optimization .In the algorithm ,we ignore the congestion factor ,it is based on the preying behavior ,supplemented by the following behavior and swarm behavior .

scholarly journals Filtered Medial Surface Based Approach for 3D Collision-Free Path Planning Problem

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Karima Benzaid ◽  
Romain Marie ◽  
Noura Mansouri ◽  
Ouiddad Labbani-Igbida
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Planning Problem ◽  
Medial Surface ◽  
Planning Approach ◽  
Aerial Vehicle ◽  
Generalized Voronoi Graph ◽  
Core Idea ◽  
Voronoi Graph ◽  
Uav Navigation

This paper introduces an original 3D path planning approach for Unmanned Aerial Vehicle (UAV) applications. More specifically, the core idea is to generate a smooth and collision-free path with respect to the vehicle dimension. Given a 3D grid representation of the environment, the Generalized Voronoi Graph (GVG) is first approximated using a filtered medial surface (FMS) algorithm on the corresponding navigable space. Based on an efficient pruning criterion, the produced FMS excludes GVG portions corresponding to narrow passages unfitting safe UAV navigation constraints, and thus it defines a set of guaranteed safe trajectories within the environment. Given a set of starting and destination coordinates, an adapted A-star algorithm is then applied to compute the shortest path on the FMS. Finally, an optimization process ensures the smoothness of the final path by fitting a set of 3D Bézier curves to the initial path. For a comparative study, the A-star algorithm is applied directly on the input environment representation and relevant comparative criteria are defined to assert the proposed approach using simulation results.

Collision-free path planning for nonholonomic mobile robots using a new obstacle representation in the velocity space

Robotica ◽  
2001 ◽  
Vol 19 (5) ◽  
pp. 543-555 ◽  
Author(s):  
Gabriel Ramírez ◽  
Saïd Zeghloul
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Nonholonomic Constraints ◽  
Linear Constraints ◽  
Velocity Space ◽  
Mobile Robot Navigation ◽  
Planning Problem ◽  
Nonholonomic Mobile Robots ◽  
Distance Information ◽  
Path Planner

This paper presents a collision-free path planner for mobile robot navigation in an unknown environment subject to nonholonomic constraints. This planner is well adapted for use with embarked sensors, because it uses only the distance information between the robot and the obstacles. The collision-free path-planning is based on a new representation of the obstacles in the velocity space. The obstacles in the influence zone are mapped as linear constraints into the velocity space of the robot, forming a convex subset that represents the velocities that the robot can use without collision with the objects. The planner is composed by two modules, termed “reaching the goal” and “boundary following”. The major advantages of this method are the very short calculation time and a continuous stable behavior of the velocities. The results presented demonstrate the capabilities of the proposed method for solving the collision-free path-planning problem.

Research on Path Planning for Mobile Robot Based on Grid and Hybrid of GA/SA

2012 ◽  
Vol 479-481 ◽  
pp. 1499-1503 ◽  
Author(s):  
Wen Jun Yang ◽  
Huai Bin Wang ◽  
Jing Hui Wang
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Grid Method ◽  
Environmental Modeling ◽  
Planning Problem ◽  
Mutation Probability ◽  
Robot Technology ◽  
Crossover And Mutation ◽  
Path Planning Problem ◽  
Technology Area

Path planning is the kernel problem of the robot technology area. In this paper, the grid method is used to make environmental modeling, Since the Genetic Algorithm (GA) has its immanent limitations and the Simulated Annealing (SA) Algorithm has the advantages in some aspects, combined these two algorithms together just achieve the perfection. In view of this, a hybrid of GA and SA (GA-SA Hybrid) is proposed in this paper to solve path planning problem for mobile robot. The algorithm making the crossover and mutation probability adjusted adaptively and nonlinearly with the completion time, can avoid such disadvantages as premature convergence. The new algorithm has better capability of searching globally and locally. The simulation results demonstrate that the proposed algorithm is valid and effective.

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