机械臂的轨迹规划与优化算法研究
摘 要
机械臂作为现代工业自动化系统中的关键执行机构，其轨迹规划与优化算法的研究对提高生产效率和作业精度具有重要意义。本文针对现有机械臂轨迹规划方法中存在的路径平滑性不足、计算复杂度高及实时性差等问题，提出了一种基于改进B样条曲线的轨迹规划与优化算法。该算法首先利用B样条曲线构建初始轨迹，通过引入自适应调整因子优化控制点分布，确保轨迹在满足关节运动学约束的同时具备良好的平滑性和可控性；然后采用多目标粒子群优化算法对轨迹进行全局优化，在保证轨迹平滑性的基础上最小化能量消耗并缩短运动时间。实验结果表明，所提出的算法能够有效生成符合要求的机械臂运动轨迹，相比传统方法，新算法在轨迹平滑性方面提升了30%，计算效率提高了45%，并且能够在更短时间内完成相同任务，显著改善了机械臂的工作性能。
关键词：机械臂轨迹规划 B样条曲线 自适应调整因子
Abstract
As the key actuator in modern industrial automation system, the research of trajectory planning and optimization algorithm is important to improve production efficiency and operation accuracy. This paper presents a trajectory planning and optimization algorithm based on the improved B spline, including insufficient high path smoothness and poor real-time calculation complexity. The algorithm first uses B spline curve to construct the initial trajectory, and introduces the adaptive adjustment factor to optimize the smoothness and controllability while the trajectory meets the joint kinematic constraints, and then uses the multi-target particle swarm optimization algorithm to optimize the trajectory to minimize the energy consumption and shorten the movement time on the basis of ensuring the trajectory smoothness. The experimental results show that the proposed algorithm can effectively generate the required trajectory of the robotic arm. Compared with the traditional method, the new algorithm improves the smoothness of the trajectory by 30%, improves the computing efficiency by 45%, and can complete the same task in a shorter time, significantly improving the performance of the robotic arm.
Keyword:Trajectory Planning Of Manipulator B-Spline Curve Adaptive Adjustment Factor
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状综述 1
1.3本文研究方法概述 1
2轨迹规划的数学模型构建 2
2.1机械臂运动学分析 2
2.2关节空间与笛卡尔空间转换 2
2.3约束条件的数学描述 3
2.4模型验证与误差分析 4
3轨迹优化算法设计 4
3.1常用优化算法比较 4
3.2目标函数构建原则 5
3.3约束处理技术探讨 5
3.4算法性能评估指标 6
4实验验证与结果分析 6
4.1实验平台搭建 6
4.2不同场景下的实验测试 7
4.3结果对比与分析 7
4.4应用前景展望 8
结论 8
参考文献 10
致谢 11
摘 要
机械臂作为现代工业自动化系统中的关键执行机构，其轨迹规划与优化算法的研究对提高生产效率和作业精度具有重要意义。本文针对现有机械臂轨迹规划方法中存在的路径平滑性不足、计算复杂度高及实时性差等问题，提出了一种基于改进B样条曲线的轨迹规划与优化算法。该算法首先利用B样条曲线构建初始轨迹，通过引入自适应调整因子优化控制点分布，确保轨迹在满足关节运动学约束的同时具备良好的平滑性和可控性；然后采用多目标粒子群优化算法对轨迹进行全局优化，在保证轨迹平滑性的基础上最小化能量消耗并缩短运动时间。实验结果表明，所提出的算法能够有效生成符合要求的机械臂运动轨迹，相比传统方法，新算法在轨迹平滑性方面提升了30%，计算效率提高了45%，并且能够在更短时间内完成相同任务，显著改善了机械臂的工作性能。
关键词：机械臂轨迹规划 B样条曲线 自适应调整因子
Abstract
As the key actuator in modern industrial automation system, the research of trajectory planning and optimization algorithm is important to improve production efficiency and operation accuracy. This paper presents a trajectory planning and optimization algorithm based on the improved B spline, including insufficient high path smoothness and poor real-time calculation complexity. The algorithm first uses B spline curve to construct the initial trajectory, and introduces the adaptive adjustment factor to optimize the smoothness and controllability while the trajectory meets the joint kinematic constraints, and then uses the multi-target particle swarm optimization algorithm to optimize the trajectory to minimize the energy consumption and shorten the movement time on the basis of ensuring the trajectory smoothness. The experimental results show that the proposed algorithm can effectively generate the required trajectory of the robotic arm. Compared with the traditional method, the new algorithm improves the smoothness of the trajectory by 30%, improves the computing efficiency by 45%, and can complete the same task in a shorter time, significantly improving the performance of the robotic arm.
Keyword:Trajectory Planning Of Manipulator B-Spline Curve Adaptive Adjustment Factor
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状综述 1
1.3本文研究方法概述 1
2轨迹规划的数学模型构建 2
2.1机械臂运动学分析 2
2.2关节空间与笛卡尔空间转换 2
2.3约束条件的数学描述 3
2.4模型验证与误差分析 4
3轨迹优化算法设计 4
3.1常用优化算法比较 4
3.2目标函数构建原则 5
3.3约束处理技术探讨 5
3.4算法性能评估指标 6
4实验验证与结果分析 6
4.1实验平台搭建 6
4.2不同场景下的实验测试 7
4.3结果对比与分析 7
4.4应用前景展望 8
结论 8
参考文献 10
致谢 11
