Multi-Objective Optimal Trajectory Planning for Woodworking Manipulator and Worktable Based on the INSGA-II Algorithm

The manipulator has been widely used in the wood processing industry; the main problem currently faced is optimizing the motion trajectory to enhance the processing efficiency and operational stability of the woodworking manipulator and worktable. A 5-7-5 piecewise polynomial interpolation method is proposed to construct the spatial trajectories of each joint. An improved non-dominated sorting genetic algorithm (INSGA-II) is proposed to achieve a time–jerk multi-objective trajectory planning that can meet the dual requirements of minimal processing time and reduced motion impact. In order to address the limitations of the standard NSGA-II algorithm, which is prone to local optima and exhibits slow convergence, we propose a good point set method for multi-objective optimization population initialization and a linear ranking selection method to refine the parent selection process within the genetic algorithm. The improved NSGA-II algorithm markedly enhanced both the uniformity of the population distribution and convergence speed. In practical applications, selecting suitable weightings to construct a normalized weight function can identify the optimal solution from the Pareto frontier curve. A high-order continuous and smooth optimal trajectory without abrupt changes can be obtained. The simulation results demonstrated that the 5-7-5 piecewise polynomial interpolation curve effectively constructed a high-order smooth processing trajectory with continuous and smooth velocity, acceleration, and jerk, free from discontinuities. Moreover, the INSGA-II algorithm outperforms the original algorithm in terms of convergence and distribution, enabling the optimal time–jerk multi-objective trajectory planning that adheres to constraint conditions. Optimized by the improved NSGA-II algorithm, the optimal total running time is 4.5400 s, and the optimal jerk is 17.934 m(rad)/s3. This provides a novel approach to solving the inefficiencies and operational instability prevalent in traditional woodworking equipment.

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Publication Details

Journal
Applied Sciences
Published
2024-12-31
DOI
https://doi.org/10.3390/app15010310
Citations
5
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
1.25

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article

Multi-Objective Optimal Trajectory Planning for Woodworking Manipulator and Worktable Based on the INSGA-II Algorithm

Hang Yu, Sihan Chen, Qinglong Dai, Jiaping Yi et al.
5 citations
Applied Sciences
Robotic Path Planning Algorithms
1.25
article

Multi-Objective Optimal Trajectory Planning for Woodworking Manipulator and Worktable Based on the INSGA-II Algorithm

Hang Yu, Sihan Chen, Qinglong Dai, Jiaping Yi, Changqing Zhang, Lei Yu, Guang Yang
article en
5 citations

Abstract

The manipulator has been widely used in the wood processing industry; the main problem currently faced is optimizing the motion trajectory to enhance the processing efficiency and operational stability of the woodworking manipulator and worktable. A 5-7-5 piecewise polynomial interpolation method is proposed to construct the spatial trajectories of each joint. An improved non-dominated sorting genetic algorithm (INSGA-II) is proposed to achieve a time–jerk multi-objective trajectory planning that can meet the dual requirements of minimal processing time and reduced motion impact. In order to address the limitations of the standard NSGA-II algorithm, which is prone to local optima and exhibits slow convergence, we propose a good point set method for multi-objective optimization population initialization and a linear ranking selection method to refine the parent selection process within the genetic algorithm. The improved NSGA-II algorithm markedly enhanced both the uniformity of the population distribution and convergence speed. In practical applications, selecting suitable weightings to construct a normalized weight function can identify the optimal solution from the Pareto frontier curve. A high-order continuous and smooth optimal trajectory without abrupt changes can be obtained. The simulation results demonstrated that the 5-7-5 piecewise polynomial interpolation curve effectively constructed a high-order smooth processing trajectory with continuous and smooth velocity, acceleration, and jerk, free from discontinuities. Moreover, the INSGA-II algorithm outperforms the original algorithm in terms of convergence and distribution, enabling the optimal time–jerk multi-objective trajectory planning that adheres to constraint conditions. Optimized by the improved NSGA-II algorithm, the optimal total running time is 4.5400 s, and the optimal jerk is 17.934 m(rad)/s3. This provides a novel approach to solving the inefficiencies and operational instability prevalent in traditional woodworking equipment.

Applied SciencesVol. 15(1)
Institute of Forest Resource Information Techniques (CN), Chinese Academy of Forestry (CN), Research Institute of Wood Industry (CN)
National Key Research and Development Program of China
Industry, innovation and infrastructure
Openalex Percentile: Top 18%
Robotic Path Planning Algorithms
1.25
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