Robot Path Planning Based on Genetic Algorithm Fused with Continuous Bezier Optimization

In this study, a new method of smooth path planning is proposed based on Bezier curves and is applied to solve the problem of redundant nodes and peak inflection points in the path planning process of traditional algorithms. First, genetic operations are used to obtain the control points of the Bezi...

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Bibliographic Details
Published in:Computational intelligence and neuroscience 2020, Vol.2020 (2020), p.1-10
Main Authors: Wang, Lin, Zang, Shaofei, Liu, Yang, Ma, Jianwei
Format: Article
Language:English
Subjects:
Adaptive control
Algorithms
Computer Simulation
Curves
Genetic algorithms
Inflection points
Methods
Mutation
Optimization
Path planning
Planning
Robotics - methods
Robots
Walking
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Summary:In this study, a new method of smooth path planning is proposed based on Bezier curves and is applied to solve the problem of redundant nodes and peak inflection points in the path planning process of traditional algorithms. First, genetic operations are used to obtain the control points of the Bezier curve. Second, a shorter path is selected by an optimization criterion that the length of the Bezier curve is determined by the control points. Finally, a safe distance and adaptive penalty factor are introduced into the fitness function to ensure the safety of the walking process of the robot. Numerous experiments are implemented in two different environments and compared with the existing methods. It is proved that the proposed method is more effective to generate a shorter, smoother, and safer path compared with traditional approaches.
ISSN:1687-5265
1687-5273
DOI:10.1155/2020/9813040