0去购物车结算
购物车中还没有商品,赶紧选购吧!
当前位置: > 工业机器人精度补偿技术与应用(英文版)

相同语种的商品

浏览历史

工业机器人精度补偿技术与应用(英文版)


联系编辑
 
标题:
 
内容:
 
联系方式:
 
  
工业机器人精度补偿技术与应用(英文版)
  • 书号:9787030740182
    作者:廖文和,李波,田威,李鹏程
  • 外文书名:
  • 装帧:平装
    开本:B5
  • 页数:231
    字数:
    语种:en
  • 出版社:科学出版社
    出版时间:2023-01-01
  • 所属分类:
  • 定价: ¥169.00元
    售价: ¥133.51元
  • 图书介质:
    纸质书

  • 购买数量: 件  可供
  • 商品总价:

相同系列
全选

内容介绍

样章试读

用户评论

全部咨询

本书详细地介绍了工业机器人精度补偿的基础理论和关键技术,主要内容包括:机器人运动学模型建立方法和机器人定位误差分析,机器人运动学模型标定方法,机器人非运动学标定方法,机器人最优采样点规划方法等,并进一步阐述了飞机装配自动制孔系统中工业机器人精度补偿技术的应用方法,以验证该技术的有效性。
样章试读
  • 暂时还没有任何用户评论
总计 0 个记录,共 1 页。 第一页 上一页 下一页 最末页

全部咨询(共0条问答)

  • 暂时还没有任何用户咨询内容
总计 0 个记录,共 1 页。 第一页 上一页 下一页 最末页
用户名: 匿名用户
E-mail:
咨询内容:

目录

  • Contents
    Part I Theories
    Chapter 1 Introduction 3
    1.1 Background 3
    1.2 What is robot accuracy 6
    1.3 Why error compensation 8
    1.4 Early investigations and insights 9
    1.4.1 Offline calibration 10
    1.4.2 Online feedback 16
    1.5 Summary 19
    Chapter 2 Kinematic modeling 21
    2.1 Introduction 21
    2.2 Pose description and transformation 21
    2.2.1 Descriptions of position and posture 21
    2.2.2 Translation and rotation 22
    2.3 RPY angle and Euler angle 23
    2.4 Forward kinematics 26
    2.4.1 Link description and link frame 26
    2.4.2 Link transformation and forward kinematic model 27
    2.4.3 Forward kinematic model of a typical KUKA industrial robot 29
    2.5 Inverse kinematics 33
    2.5.1 Uniquely closed solution with joint constraints 34
    2.5.2 Inverse kinematic model of a typical KUKA industrial robot 35
    2.6 Error modeling 38
    2.6.1 Differential transformation 38
    2.6.2 Differential transformation of consecutive links 40
    2.6.3 Kinematic error model 42
    2.7 Summary 44
    Chapter 3 Positioning error compensation using kinematic calibration 45
    3.1 Introduction 45
    3.2 Observability-index-based random sampling method 46
    3.2.1 Observability index of robot kinematic parameters 46
    3.2.2 Selection method of sampling points 48
    3.3 Uniform-grid-based sampling method 54
    3.3.1 Optimal grid size 54
    3.3.2 Sampling point planning method 67
    3.4 Kinematic calibration considering robot flexibility error 73
    3.4.1 Robot flexibility analysis 74
    3.4.2 Establishment of robot flexibility error model 76
    3.4.3 Robot kinematic error model with flexibility error 77
    3.5 Kinematic calibration using variable parametric error 79
    3.6 Parameter identification using L-M algorithm 81
    3.7 Verification of error compensation performance 83
    3.7.1 Kinematic calibration with robot flexibility error 83
    3.7.2 Error compensation using variable parametric error 84
    3.8 Summary 91
    Chapter 4 Error-similarity-based positioning error compensation 92
    4.1 Introduction 92
    4.2 Similarity of robot positioning error 93
    4.2.1 Qualitative analysis of error similarity 93
    4.2.2 Quantitative analysis of error similarity 94
    4.2.3 Numerical simulation and discussion 96
    4.3 Error compensation based on inverse distance weighting and error similarity 100
    4.3.1 Inverse distance weighting interpolation method 101
    4.3.2 Error compensation method combined IDW with error similarity 102
    4.3.3 Numerical simulation and discussion 104
    4.4 Error compensation based on linear unbiased optimal estimation and error similarity 106
    4.4.1 Robot positioning error mapping based on error similarity 106
    4.4.2 Linear unbiased optimal estimation of robot positioning error 109
    4.4.3 Numerical simulation and discussion 112
    4.4.4 Error compensation 116
    4.5 Optimal sampling based on error similarity 116
    4.5.1 Mathematical model of optimal sampling points 117
    4.5.2 Multi-objective optimization and non-inferior solution 119
    4.5.3 Genetic algorithm and NSGA-II 121
    4.5.4 Multi-objective optimization of optimal sampling points of robots based on NSGA-II 128
    4.6 Experimental verification 131
    4.6.1 Experimental platform 131
    4.6.2 Experimental verification of positioning error similarity 133
    4.6.3 Experimental verification of error compensation based on inverse distance weighting and error similarity 141
    4.6.4 Experimental verification of error compensation based on linear unbiased optimal estimation and error similarity 145
    4.7 Summary 148
    Chapter 5 Joint space closed-loop feedback 149
    5.1 Introduction 149
    5.2 Positioning error estimation 149
    5.2.1 Error estimation model of Chebyshev polynomial 149
    5.2.2 Identification of Chebyshev coefficients 153
    5.2.3 Mapping model 154
    5.3 Effect of joint backlash on positioning error 155
    5.3.1 Variation law of joint backlash 155
    5.3.2 Multi-directional positioning accuracy variation 158
    5.4 Error compensation using feedforward and feedback loops 161
    5.5 Experimental verification and analysis 162
    5.5.1 Experimental setup 162
    5.5.2 Error estimation experiment 163
    5.5.3 Error compensation experiment 165
    5.6 Summary 167
    Chapter 6 Cartesian space closed-loop feedback 168
    6.1 Introduction 168
    6.2 Pose measurement using binocular visual sensor 168
    6.2.1 Description of frame 168
    6.2.2 Pose measurement principle based on binocular vision 170
    6.2.3 Influence of the frame FE on measurement accuracy 174
    6.2.4 Pose estimation using Kalman filtering 177
    6.3 Vision-guided control system 178
    6.4 Experimental verification 183
    6.4.1 Experimental platform 183
    6.4.2 Kalman-filtering-based estimation 184
    6.4.3 No-load experiment 185
    6.5 Summary 189
    Part II Applications
    Chapter 7 Applications in robotic drilling 193
    7.1 Introduction 193
    7.2 Robotic drilling system 193
    7.2.1 Hardware 193
    7.2.2 Software 196
    7.3 Establishment of frames 198
    7.3.1 World frame 198
    7.3.2 Robot base frame 200
    7.3.3 Robot flange frame 201
    7.3.4 Tool frame 203
    7.3.5 Product frame 204
    7.3.6 Transformation of frames 205
    7.4 Drilling applications 207
    7.4.1 Error-similarity-based error compensation 207
    7.4.2 Joint space closed-loop feedback 210
    7.4.3 Cartesian space closed-loop feedback 212
    7.5 Summary 214
    Chapter 8 Applications in robotic milling 215
    8.1 Introduction 215
    8.2 Robotic milling system 215
    8.3 Milling on aluminum alloy part 216
    8.3.1 Line milling 216
    8.3.2 Arc milling 217
    8.4 Milling on cylinder head for car engine 219
    8.4.1 Line milling 221
    8.4.2 Plane milling 222
    8.5 Edge milling on composite shell 223
    8.6 Summary 225
    References 226
帮助中心
公司简介
联系我们
常见问题
新手上路
发票制度
积分说明
购物指南
配送方式
配送时间及费用
配送查询说明
配送范围
快递查询
售后服务
退换货说明
退换货流程
投诉或建议
版权声明
经营资质
营业执照
出版社经营许可证