A Robot Path Planning Method Based on Bezier Optimization Genetic Algorithm

A genetic algorithm and path planning technology, which is applied in the field of robot path planning combined with Bezier optimization genetic algorithm, can solve the problems that the robot cannot walk according to the planned path, the energy loss of the robot, etc., and achieve excellent search performance, reduce energy loss, and move efficiently. Effect

Active Publication Date: 2022-07-12
HENAN UNIV OF SCI & TECH +1
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Problems solved by technology

Although the genetic algorithm can plan a better path under different performance indicators, there will be many problems in the actual process, such as: there are many peaks in the obtained path, which makes the robot unable to walk according to the planned path during the moving process; There are a large number of inflection points in the path, resulting in excessive energy loss for the robot, etc.

Method used

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  • A Robot Path Planning Method Based on Bezier Optimization Genetic Algorithm
  • A Robot Path Planning Method Based on Bezier Optimization Genetic Algorithm
  • A Robot Path Planning Method Based on Bezier Optimization Genetic Algorithm

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Embodiment 1

[0087] In order to reflect the feasibility and effectiveness of the algorithm, the robot path planning problems in the environment 1: 20×20 and environment 2: 10×10 grid map environment are used for verification, such as Image 6 As shown, in environment 1, the coordinates of the starting point of the robot are (0.5, 0.5), the coordinates of the end point are (19.5, 19.5), and the parameters are set as: Q=30, gn=50, N=30, Q max =30,Re=0.8,Mu=0.01,w 1 =0.9,w 2 =0.1, C=1. like Figure 7 As shown, in environment 2, the coordinates of the starting point of the robot are (0.5, 0.5), the coordinates of the end point are (9.5, 9.5), and the parameters are set as: Q=30, gn=50, N=30, Q max =30,Re=0.7,Mu=0.01,w 1 =0.9,w 2 =0.1, C=1. .

[0088] In order to examine the feasibility of the algorithm in this paper, the traditional ant colony algorithm (ACA), the traditional genetic algorithm (GA), the improved ant colony algorithm with integrated genetic operator (GA-ACO), and the int...

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Abstract

The invention relates to a robot path planning method integrating Bezier optimization genetic algorithm, which belongs to the field of artificial intelligence. The method first adopts the Bezier curve to optimize the initial solution of the genetic algorithm and the path generated in the process of crossover and mutation, so as to eliminate the peak inflection point and eliminate the peak inflection point. Reduce redundant nodes to improve the smoothness of the path; then use the fitness function with increased safety distance and adaptive penalty factor to dynamically adjust the path obtained by the genetic algorithm to improve the quality of the planned path. This method can search for a shorter and smoother path, so that the robot can reduce the energy loss caused by frequent switching of operating states due to the sharp turning of the path, and further ensure the safety of the robot's movement.

Description

technical field [0001] The invention belongs to the field of artificial intelligence, and in particular relates to a robot path planning method integrating Bezier optimization genetic algorithm. Background technique [0002] Path planning is an important research direction in the field of mobile robots, and it is also one of its research difficulties. The path planning problem can be described as: searching for a collision-free path from the starting point to the target point in an environment with obstacles according to a certain evaluation index. Path planning has been widely used in logistics distribution, intelligent transportation, weapon navigation and other fields. Therefore, the study of fast and effective path planning methods has become a focus of attention, which has high theoretical significance and practical value. [0003] Genetic algorithm is a bionic optimization algorithm. It takes natural selection, genetic inheritance and mutation in Darwin's theory of b...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/02G01C21/20
CPCG05D1/0088G05D1/0212
Inventor 马建伟刘洋张永新郑红运张瑞玲马友忠贾世杰
Owner HENAN UNIV OF SCI & TECH
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