Mobile robot path planning method based on improved A star strategy

A mobile robot, path planning technology, applied in the direction of instruments, non-electric variable control, two-dimensional position/channel control, etc., can solve the problems of insensitive environment, trapped in obstacles, unable to meet the real-time performance of robots, etc. The effect of saving memory and computing resources, and accelerating the convergence speed

Inactive Publication Date: 2018-09-18
苏州寻迹智行机器人技术有限公司
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Problems solved by technology

All heuristic-based algorithms need to model obstacles in a certain space, and usually have a slow convergence speed, which cannot meet the real-time requirements of robots.
The random sampling method avoids the modeling of the space, and finds a path with complete probability and is not optimal through random sampling points in the state space; but this type

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  • Mobile robot path planning method based on improved A star strategy
  • Mobile robot path planning method based on improved A star strategy
  • Mobile robot path planning method based on improved A star strategy

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Embodiment Construction

[0034] The present invention is based on the mobile robot path planning method of improving A star strategy, such as figure 1 As shown, it includes the following steps:

[0035] (a) Process the laser data and mileage data acquired by the mobile robot with the slam algorithm to obtain a grid map in .pgm format (each pixel is a gray value of 0-255); Figure II The value is stored in a two-dimensional array (as the input to create the Voronoi diagram, specifically, to traverse the pixels of the entire map, if value=0, then assign a value of 0, otherwise value>0 assign a value of 1); figure 2 The company's floor map obtained for the mobile robot is obtained by the slam algorithm; it generally contains two files, .pgm and .yaml; .pgm is a grayscale image containing 256 grayscale values, and .yaml is the corresponding configuration file (including image The file name, resolution and origin coordinates of the map); among them, there are three gray values ​​in the map, the white are...

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Abstract

The invention relates to a mobile robot path planning method based on improved A star strategy. The method comprises the following steps: (a) processing laser data and mileage data acquired by a mobile robot by using a slam algorithm; (b) constructing a binaryzation raster map into a Voronoi map by utilizing a dynamic weinuo graph library; (c) constructing a corresponding Voronoi cost map according to the node coordinate on the Voronoi map; (d) transferring the starting position and the final position of the mobile robot to a map coordinate, and checking whether the starting and final coordinated indexes are legal or not; and (e) initializing g cost values of all nodes; and (f) smoothing the whole discrete path by using a smoother. The memory and calculation resources are greatly saved, the algorithmic convergence rate is accelerated; the Voronoi map is fused, so that the path is far away from barriers, and finally a best path is acquired by using the smoother.

Description

technical field [0001] The invention belongs to the field of industrial robots, and relates to a path planning method for a mobile robot, in particular to a path planning method for a mobile robot based on an improved A-star strategy. Background technique [0002] The main function of global path planning is to find an optimal or nearly optimal path from the starting point to the end point on the known static map. The path is generally continuous, smooth, free of obstacles, and suitable for the global path directly executed by the robot. . Path planning algorithm is the basis of the whole navigation system, and its results provide path information for subsequent local trajectory planning. [0003] There are many path planning algorithms commonly used at present, which can be mainly divided into three categories: methods based on graph search, such as Dijkstra, A* (namely A star), D*, Theta*, etc.; methods based on random adoption, such as random path Graph method (PRM), ra...

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Application Information

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IPC IPC(8): G05D1/02
CPCG05D1/0214G05D1/0221G05D1/0223G05D1/0236G05D1/024G05D1/0253G05D1/0276
Inventor 翟冬灵葛凯张二阳
Owner 苏州寻迹智行机器人技术有限公司
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