Path planning method based on mobile robot

A mobile robot, path planning technology, applied in the directions of instruments, non-electric variable control, two-dimensional position/channel control, etc. High efficiency and short time effect

Pending Publication Date: 2020-03-06
TIANJIN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method has certain limitations, such as local minimum points, unreachable targets, and easy oscillations, which make the path planning process unable to proceed steadily.

Method used

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  • Path planning method based on mobile robot
  • Path planning method based on mobile robot
  • Path planning method based on mobile robot

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0049] 1. Environment Modeling

[0050] The environment in which the robot travels is a two-dimensional plane space, and the obstacles in the plane are set as static, random and known arbitrary irregular polygons, and its vertices (x, y) are represented by a ring list. Compared with the grid method, this method is easy to solve complex environmental information problems and occupies less resources.

[0051] 2. Dynamic parallel fitting strategy

[0052] In previous studies, the process of using Bezier curve to smooth the path is an independent process, that is, after the optimal path is generated, the Bezier curve is used for static fitting, which will increase the calculation steps and make the algorithm cumbersome. Therefore, use Q-IGA to search for the most suitable control point P as the control point of the Bezier curve, and use the selected control point to generate a shorter optimal path.

[0053] The environment model established in the method of the present invention...

Embodiment 2

[0097] Before carrying out the simulation experiment, it is first necessary to set reasonable parameters to make the algorithm obtain the optimal solution. Figure 4 (a), (b), (c), and (d) are the relationship between population size and path length, calculation time, iteration number and path length, and calculation time, respectively. Combining the four performance diagrams, it can be seen that with the increase of the population size and the number of iterations, the execution time of the algorithm continues to increase, basically showing a linear upward trend, which is in line with the relationship between the running time and the complexity of the algorithm; As the number of times increases, the path length decreases for a period of time, and after a certain node, it tends to be stable and basically unchanged. It can be seen from Figures (a) and (c) that when the population size is 110, the path length reaches stability after 150 iterations. Therefore, for the first map, ...

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Abstract

The invention discloses a path planning method based on a mobile robot. The method comprises the steps that based on a polygonal barrier planar model, Q-IGA is utilized to collaboratively search for the most appropriate control point P which serves as a control point of a Bezier curve, and the control point is utilized to generate an optimal path; the difference between difference paths in a population in each iteration is calculated, a judgment criterion is added to a selection operator for optimization, and the diversity of feasible solutions in the population is guaranteed; and a fitness function considering a barrier distance, a turning angle and a robot volume is constructed with the optimization objective of a maximum fitness function value. Through the method, the situation that steps are tedious when the optimal path is obtained through direct fitting search by use of the Bezier curve in robot path planning is avoided, it is guaranteed that the path planning process is completed efficiently, consumed time is short, and path planning efficiency is higher.

Description

technical field [0001] The invention relates to the field of artificial intelligence, in particular to a path planning method based on a mobile robot. Background technique [0002] With the development and maturity of many interdisciplinary subjects such as computer technology, control theory, sensor technology and artificial intelligence, self-navigating robot technology has developed rapidly, and various robots are used in many fields such as scientific research, industrial production, and home life. [1] . Self-navigating robot technology is not only the cornerstone of mobile robots to complete difficult tasks, but also an important symbol of the maturity of robot intelligence [2] . Algorithms for controlling the motion of a self-navigating robot [3] It is mainly composed of three parts: positioning algorithm, navigation control algorithm and path planning algorithm. Safe obstacle avoidance in the path search process is the prerequisite for the robot to successfully co...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
CPCG05D1/0223G05D1/0214G05D1/0221G05D1/0276
Inventor 徐岩崔媛媛
Owner TIANJIN UNIV
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