机器人末端执行器的设计与优化研究
摘 要
机器人末端执行器作为机器人系统与环境交互的关键部件，其性能直接影响机器人的作业精度和效率。随着工业自动化、医疗手术、空间探索等领域对机器人灵活性和适应性的要求日益提高，传统末端执行器难以满足复杂任务需求，亟需创新设计与优化方法。本研究旨在通过多学科交叉融合，提出一种基于模块化结构和智能感知的新型末端执行器设计方案，并建立相应的优化模型。采用有限元分析结合遗传算法对结构参数进行全局寻优，同时引入深度学习算法实现对抓取对象特征的自适应识别与调整。实验结果表明，所设计的末端执行器在抓取成功率、负载能力及响应速度等方面较传统方案有显著提升，特别是在处理非规则形状物体时表现出优异的适应性。
关键词：机器人末端执行器 模块化结构 智能感知
Abstract
As the key component of the robot system and the environment, the performance of the robot end-effector directly affects the accuracy and efficiency of the robot. With the increasing requirements for robot flexibility and adaptability in the fields of industrial automation, medical surgery, space exploration and so on, traditional end-actuators can hardly meet the needs of complex tasks, and innovative design and optimization methods are urgently needed. This study aims to propose a novel end-effector design scheme based on modular structure and intelligent perception, and establish corresponding optimization models. Finite element analysis and genetic algorithm are used to globally optimize the structural parameters, and a deep learning algorithm is introduced to realize the adaptive recognition and adjustment of the features of grasping ob jects. The experimental results show that the designed end effector is significantly improved in grasping success rate, load capacity and response speed compared with the traditional scheme, especially showing excellent adaptability in dealing with irregular shaped ob jects.
Keyword:Robot End Effector Modular Structure Intelligent Perception
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研究方法与技术路线 2
2末端执行器功能需求分析 2
2.1工业应用需求特点 2
2.2特殊环境适应性要求 3
2.3多任务执行能力分析 3
3末端执行器结构设计优化 4
3.1关键部件选型依据 4
3.2运动学特性优化 4
3.3力学性能提升策略 5
4末端执行器控制系统集成 6
4.1控制系统架构设计 6
4.2传感器融合技术 6
4.3实时控制算法优化 7
结论 8
参考文献 9
致谢 10
摘 要
机器人末端执行器作为机器人系统与环境交互的关键部件，其性能直接影响机器人的作业精度和效率。随着工业自动化、医疗手术、空间探索等领域对机器人灵活性和适应性的要求日益提高，传统末端执行器难以满足复杂任务需求，亟需创新设计与优化方法。本研究旨在通过多学科交叉融合，提出一种基于模块化结构和智能感知的新型末端执行器设计方案，并建立相应的优化模型。采用有限元分析结合遗传算法对结构参数进行全局寻优，同时引入深度学习算法实现对抓取对象特征的自适应识别与调整。实验结果表明，所设计的末端执行器在抓取成功率、负载能力及响应速度等方面较传统方案有显著提升，特别是在处理非规则形状物体时表现出优异的适应性。
关键词：机器人末端执行器 模块化结构 智能感知
Abstract
As the key component of the robot system and the environment, the performance of the robot end-effector directly affects the accuracy and efficiency of the robot. With the increasing requirements for robot flexibility and adaptability in the fields of industrial automation, medical surgery, space exploration and so on, traditional end-actuators can hardly meet the needs of complex tasks, and innovative design and optimization methods are urgently needed. This study aims to propose a novel end-effector design scheme based on modular structure and intelligent perception, and establish corresponding optimization models. Finite element analysis and genetic algorithm are used to globally optimize the structural parameters, and a deep learning algorithm is introduced to realize the adaptive recognition and adjustment of the features of grasping ob jects. The experimental results show that the designed end effector is significantly improved in grasping success rate, load capacity and response speed compared with the traditional scheme, especially showing excellent adaptability in dealing with irregular shaped ob jects.
Keyword:Robot End Effector Modular Structure Intelligent Perception
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研究方法与技术路线 2
2末端执行器功能需求分析 2
2.1工业应用需求特点 2
2.2特殊环境适应性要求 3
2.3多任务执行能力分析 3
3末端执行器结构设计优化 4
3.1关键部件选型依据 4
3.2运动学特性优化 4
3.3力学性能提升策略 5
4末端执行器控制系统集成 6
4.1控制系统架构设计 6
4.2传感器融合技术 6
4.3实时控制算法优化 7
结论 8
参考文献 9
致谢 10
