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 The Robot Path Planning Based on Improved Artificial Fish Swarm Algorithm

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Yi Zhang ◽  
Guolun Guan ◽  
Xingchen Pu
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Planning Problem ◽  
Robot Path Planning ◽  
Ideal Convergence ◽  
Artificial Fish Swarm Algorithm ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm ◽  
Searching Ability ◽  
Robot Path

Path planning is critical to the efficiency and fidelity of robot navigation. The solution of robot path planning is to seek a collision-free and the shortest path from the start node to target node. In this paper, we propose a new improved artificial fish swarm algorithm (IAFSA) to process the mobile robot path planning problem in a real environment. In IAFSA, an attenuation function is introduced to improve the visual of standard AFSA and get the balance of global search and local search; also, an adaptive operator is introduced to enhance the adaptive ability of step. Besides, a concept of inertia weight factor is proposed in IAFSA inspired by PSO intelligence algorithm to improve the convergence rate and accuracy of IAFSA. Five unconstrained optimization test functions are given to illustrate the strong searching ability and ideal convergence of IAFSA. Finally, the ROS (robot operation system) based experiment is carried out on a Pioneer 3-DX mobile robot; the experiment results also show the superiority of IAFSA.

Mobile Robot Path Planning Based on Ant Colony Optimization

2014 ◽  
Vol 687-691 ◽  
pp. 706-709
Author(s):  
Bao Feng Zhang ◽  
Ya Chun Wang ◽  
Xiao Ling Zhang
Keyword(s):  
Path Planning ◽  
High Performance ◽  
Ant Colony Algorithm ◽  
Optimal Path ◽  
Grid Method ◽  
Ant Colony ◽  
Infrared Sensors ◽  
Object Based ◽  
Starting Point ◽  
Robot Path

Global path planning is quoted in this paper. The stoical and global environment has been given to us, which is abstracted with grid method before we build the workspace model of the robot. With the adoption of the ant colony algorithm, the robot tries to find a path which is optimal or optimal-approximate path from the starting point to the destination. The robot with the built-in infrared sensors navigates autonomously to avoid collision the optimal path which has been built, and moves to the object. Based on the MATLAB platform, the simulation results indicate that the algorithm is rapid, simple, efficient and high-performance. Majority of traditional algorithms of the path planning have disadvantages, for instance, the method of artificial potential field is falling into the problem of local minimum value easily. ACO avoids these drawbacks, therefore the convergence period can be extended, and optimal path can be planned rapidly.

scholarly journals Mobile robot path planning in dynamic environment based on cuckoo optimization algorithm

2019 ◽  
Vol 16 (2) ◽  
pp. 172988141983957 ◽  
Author(s):  
Seyedhadi Hosseininejad ◽  
Chitra Dadkhah
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Free Path ◽  
Optimization Algorithm ◽  
Dynamic Environment ◽  
Planning Problem ◽  
Robot Path Planning ◽  
Cuckoo Optimization Algorithm ◽  
Starting Point ◽  
Robot Path

Nowadays, the usage of autonomous mobile robots that fulfill various activities in enormous number of applications without human’s interference in a dynamic environment are thriving. A dynamic environment is the robot’s environment which is comprised of some static obstacles as well as several movable obstacles that their quantity and location change randomly through the time. Efficient path planning is one the significant necessities of these kind of robots to do their tasks effectively. Mobile robot path planning in a dynamic environment is finding a shortest possible path from an arbitrary starting point toward a desired goal point which needs to be safe (obstacle avoidance) and smooth as well as possible. To achieve this target, simultaneously satisfying a collection of certain constraints including the shortest, smooth, and collision free path is required. Therefore, this issue can be considered as an optimization problem, consequently solved via optimization algorithms. In this article, a new method based on cuckoo optimization algorithm is proposed for solving the mobile robot path planning problem in a dynamic environment. Furthermore, to diminish the computational complexity, the feature vector is also optimized (i.e. reduced in dimension) via a new proposed technique. The simulation results show the performance of proposed algorithm in finding a short, safe, smooth, and collision free path in different environment conditions.

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.

Three Dimensional Robot Path Planning With Workspace Considerations

1992 ◽  
Author(s):  
C. Y. Liu ◽  
R. W. Mayne
Keyword(s):  
Path Planning ◽  
Three Dimensional ◽  
Optimization Methods ◽  
Planning Problem ◽  
Robot Path Planning ◽  
Recursive Quadratic Programming ◽  
Six Degree Of Freedom ◽  
Nonlinear Programming Method ◽  
Path Planning Problem ◽  
Robot Path

Abstract This paper considers the problem of robot path planning by optimization methods. It focuses on the use of recursive quadratic programming (RQP) for the optimization process and presents a formulation of the three dimensional path planning problem developed for compatibility with the RQP selling. An approach 10 distance-to-contact and interference calculations appropriate for RQP is described as well as a strategy for gradient computations which are critical to applying any efficient nonlinear programming method. Symbolic computation has been used for general six degree-of-freedom transformations of the robot links and to provide analytical derivative expressions. Example problems in path planning are presented for a simple 3-D robot. One example includes adjustments in geometry and introduces the concept of integrating 3-D path planning with geometric design.

scholarly journals Research and Implementation of Robot Path Planning Based onVSLAM

2018 ◽  
Vol 160 ◽  
pp. 06004
Author(s):  
Zi-Qiang Wang ◽  
He-Gen Xu ◽  
You-Wen Wan
Keyword(s):  
Path Planning ◽  
Three Dimensional ◽  
Planning Problem ◽  
A Algorithm ◽  
Algorithm Efficiency ◽  
Grid Map ◽  
Localization And Mapping ◽  
Improve Algorithm ◽  
Path Planning Problem ◽  
Robot Path

In order to solve the problem of warehouse logistics robots planpath in different scenes, this paper proposes a method based on visual simultaneous localization and mapping (VSLAM) to build grid map of different scenes and use A* algorithm to plan path on the grid map. Firstly, we use VSLAMto reconstruct the environment in three-dimensionally. Secondly, based on the three-dimensional environment data, we calculate the accessibility of each grid to prepare occupied grid map (OGM) for terrain description. Rely on the terrain information, we use the A* algorithm to solve path planning problem. We also optimize the A* algorithm and improve algorithm efficiency. Lastly, we verify the effectiveness and reliability of the proposed method by simulation and experimental results.

Sign in / Sign up

Export Citation Format

Share Document