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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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Robot Path Planning Based on Genetic Algorithm Fused with Continuous Bezier Optimization.

Jianwei Ma1, Yang Liu1, Shaofei Zang1

  • 1School of Information Engineering, Henan University of Science and Technology, Luoyang 471023, Henan, China.

Computational Intelligence and Neuroscience
|March 19, 2020
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Summary
This summary is machine-generated.

This study introduces a novel Bezier curve path planning method, enhancing robot navigation by reducing redundant nodes and improving path smoothness and safety. The approach optimizes control points for shorter, safer robot movements.

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Area of Science:

  • Robotics
  • Computer Science
  • Artificial Intelligence

Background:

  • Traditional path planning algorithms often suffer from issues like redundant nodes and peak inflection points.
  • These limitations can lead to inefficient and jerky robot movements, impacting navigation performance.

Purpose of the Study:

  • To propose a new smooth path planning method using Bezier curves.
  • To address and overcome the limitations of traditional path planning algorithms, specifically redundant nodes and peak inflection points.
  • To enhance the safety and efficiency of robot navigation.

Main Methods:

  • Utilizing genetic operations to determine Bezier curve control points.
  • Employing an optimization criterion based on Bezier curve length, determined by control points, to select shorter paths.
  • Integrating a safe distance and adaptive penalty factor into the fitness function for enhanced safety.

Main Results:

  • The proposed Bezier curve-based method generates shorter and smoother paths compared to traditional algorithms.
  • Experimental results in diverse environments demonstrate the effectiveness of the new approach.
  • The method successfully ensures a safe walking process for the robot.

Conclusions:

  • The novel Bezier curve path planning method offers significant improvements over traditional approaches.
  • The technique effectively produces shorter, smoother, and safer paths for robot navigation.
  • This method provides a robust solution for complex path planning challenges in robotics.