Modeling and Error Compensation of Robotic Articulated Arm Coordinate Measuring Machines Using BP Neural Network
Articulated arm coordinate measuring machine (AACMM) is a specific robotic structural instrument, which uses D-H method for the purpose of kinematic modeling and error compensation. However, it is difficult for the existing error compensation models to describe various factors, which affects the acc...
Saved in:
Main Authors: | Guanbin Gao, Hongwei Zhang, Hongjun San, Xing Wu, Wen Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2017-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2017/5156264 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Kinematics and Workspace Analysis for Articulated Arm Coordinate Measuring Machine
by: Zhou Aiguo, et al.
Published: (2015-01-01) -
Articulated Arm Coordinate Measuring Machine Calibration by Laser Tracker Multilateration
by: Jorge Santolaria, et al.
Published: (2014-01-01) -
Research on End-Effector Position Error Compensation of Industrial Robotic Arm Based on ECOA-BP
by: Wenping Xiang, et al.
Published: (2025-01-01) -
Research of the Robot Arm Gravity Compensation based on the Genetic Algorithm for Optimization of Neural Network
by: Yang Yuan, et al.
Published: (2017-01-01) -
Compensation of the Radial Error of Measuring Head based on Forming Grinding Machine
by: Wang Zhonghou, et al.
Published: (2017-01-01)