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.

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.

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.

Multi Objective Path Finding Based on Adding-Weight A* Algorithm

2014 ◽  
Vol 1079-1080 ◽  
pp. 711-715 ◽  
Author(s):  
Qiang Wang ◽  
Guan Cheng Wang ◽  
Fan Fei ◽  
Shuai Lü
Keyword(s):  
Path Planning ◽  
Operation Time ◽  
Planning Problem ◽  
Search Efficiency ◽  
A Algorithm ◽  
List Structure ◽  
Initial Node ◽  
Multi Objective ◽  
Linked List ◽  
Path Planning Problem

Multi-objective path planning is a path planning problem when there are more than one objective function to be optimized at the same time. This paper is based on traditional A* algorithm.To improve the algorithm A* and find out the shortest path in the different environments,we choose different weights and do global path planning by using improved evaluation function.We use the minimum binary heap in a linked list structure to manage the OPEN table,and the search efficiency has been improved.We compile the simulation program of path planning in the VC environment,then compare the operation time and generated paths by transforming the coordinates of the initial node and the goal node.Research shows that, the algorithm can improve the efficiency of the path planning efficiently.

Application of Particle Swarm Optimization to Robot Path Planning Problem

2010 ◽  
Author(s):  
Masakazu Kobayashi ◽  
Higashi Masatake
Keyword(s):  
Particle Swarm Optimization ◽  
Path Planning ◽  
Particle Swarm ◽  
Degree Of Freedom ◽  
Planning Problem ◽  
Robot Path Planning ◽  
Swarm Optimization ◽  
Articulated Robot ◽  
Path Planning Problem ◽  
Robot Path

A robot path planning problem is to produce a path that connects a start configuration and a goal configuration while avoiding collision with obstacles. To obtain a path for robots with high degree of freedom of motion such as an articulated robot efficiently, sampling-based algorithms such as probabilistic roadmap (PRM) and rapidly-exploring random tree (RRT) were proposed. In this paper, a new robot path planning method based on Particle Swarm Optimization (PSO), which is one of heuristic optimization methods, is proposed in order to improve efficiency of path planning for a wider range of problems. In the proposed method, a group of particles fly through a configuration space while avoiding collision with obstacles and a collection of their trajectories is regarded as a roadmap. A velocity of each particle is updated for every time step based on the update equation of PSO. After explaining the details of the proposed method, this paper shows the comparisons of efficiency between the proposed method and RRT for 2D maze problems and then shows application of the proposed method to path planning for a 6 degree of freedom articulated robot.

2-Degree-of-freedom Robot Path Planning using Cooperative Neural Fields

1991 ◽  
Vol 3 (3) ◽  
pp. 350-362 ◽  
Author(s):  
Michael Lemmon
Keyword(s):  
Neural Network ◽  
Path Planning ◽  
Oscillatory Behavior ◽  
Degree Of Freedom ◽  
Planning Problem ◽  
Neural Fields ◽  
Dynamic Programming Equation ◽  
Two Degree Of Freedom ◽  
Path Planning Problem ◽  
Robot Path

This paper proposes a neural network solution to path planning by two degree-of-freedom (DOF) robots. The proposed network is a two-dimensional sheet of neurons forming a distributed representation of the robot's workspace. Lateral interconnections between neurons are “cooperative,” so that the field exhibits oscillatory behavior. This paper shows how that oscillatory behavior can be used to solve the path-planning problem. The results reported show that the proposed neural network finds the variational solution of Bellman's dynamic programming equation.

scholarly journals A Novel Three-Dimensional Path Planning Method for Fixed-Wing UAV Using Improved Particle Swarm Optimization Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Chen Huang
Keyword(s):  
Particle Swarm Optimization ◽  
Path Planning ◽  
Three Dimensional ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Planning Problem ◽  
Dimensional Problem ◽  
Complex Environment ◽  
Swarm Optimization ◽  
Path Planning Problem

This paper proposed an improved particle swarm optimization (PSO) algorithm to solve the three-dimensional problem of path planning for the fixed-wing unmanned aerial vehicle (UAV) in the complex environment. The improved PSO algorithm (called DCA ∗ PSO) based dynamic divide-and-conquer (DC) strategy and modified A ∗ algorithm is designed to reach higher precision for the optimal flight path. In the proposed method, the entire path is divided into multiple segments, and these segments are evolved in parallel by using DC strategy, which can convert the complex high-dimensional problem into several parallel low-dimensional problems. In addition, A ∗ algorithm is adopted to generated an optimal path from the particle swarm, which can avoid premature convergence and enhance global search ability. When DCA ∗ PSO is used to solve the large-scale path planning problem, an adaptive dynamic strategy of the segment selection is further developed to complete an effective variable grouping according to the cost. To verify the optimization performance of DCA ∗ PSO algorithm, the real terrain data is utilized to test the performance for the route planning. The experiment results show that the proposed DCA ∗ PSO algorithm can effectively obtain better optimization results in solving the path planning problem of UAV, and it takes on better optimization ability and stability. In addition, DCA ∗ PSO algorithm is proved to search a feasible route in the complex environment with a large number of the waypoints by the experiment.

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