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<p>To address the issues of trajectory smoothness and deficiencies in complex shape approximation, as well as the lack of impact optimization in the high-speed spraying process of turbine blade robots, the focus is placed on the trajectory planning and optimization of the turning and switching sections in multi-pass high-speed spraying operations on the concave surfaces of turbine blades. A trajectory planning method for spray robots based on intelligent optimization algorithms and seventh-degree non-uniform B-spline interpolation methods is proposed. Time, energy, and impact are set as optimization objectives, and intelligent optimization algorithms are employed to adjust the weight coefficients of the seventh-order non-uniform B-spline interpolation method, resulting in a desirable multi-objective optimized solution. This approach ensures high approximation accuracy and smoothness for complex shapes while achieving multi-objective hybrid optimization for time, energy, and impact, significantly enhancing spray quality. The feasibility of this method is demonstrated through simulation and experimental validation, indicating broad application prospects in design and production, and providing new strategic directions for the intelligent development of robotic processing.</p>

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A Multi-Objective Optimization-Based Robot Coating Trajectory Planning Algorithm for Combustion Turbine Blades Using Seventh-Degree Non-Uniform B-Spline Curves

  • 期刊论文

  • 发表日期：

    2025年5月5日

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  • Xuejian Zhang,
  • Zheyuan Zhang,
  • Le Ling,
  • Xiaobing Hu,
  • Dongming Yang,
  • Hang Li,
  • Yucong Fu,
  • Enpei Liang

摘要

To address the issues of trajectory smoothness and deficiencies in complex shape approximation, as well as the lack of impact optimization in the high-speed spraying process of turbine blade robots, the focus is placed on the trajectory planning and optimization of the turning and switching sections in multi-pass high-speed spraying operations on the concave surfaces of turbine blades. A trajectory planning method for spray robots based on intelligent optimization algorithms and seventh-degree non-uniform B-spline interpolation methods is proposed. Time, energy, and impact are set as optimization objectives, and intelligent optimization algorithms are employed to adjust the weight coefficients of the seventh-order non-uniform B-spline interpolation method, resulting in a desirable multi-objective optimized solution. This approach ensures high approximation accuracy and smoothness for complex shapes while achieving multi-objective hybrid optimization for time, energy, and impact, significantly enhancing spray quality. The feasibility of this method is demonstrated through simulation and experimental validation, indicating broad application prospects in design and production, and providing new strategic directions for the intelligent development of robotic processing.