<title>Flexible workobject localization for CAD-based robotics</title>
Mikko Sallinen, Tapio Heikkilä
- 发表年份
- 2000
- 引用次数
- 13
摘要
In this paper a method to locate work objects with splined surfaces and estimate the spatial uncertainties of the estimated parameters is presented. The reference B-spline surface patch is selected from a work object CAD-model and is defined in the form of control vertices. The process includes the hang-eye calibration of the sensor, determination of the work object localization and surface treating, e.g. inspection. The hand-eye calibration and work object localization are carried out using the Bayesian form estimation with sensor fusion. Use of the recursive sensor fusion method makes calibration more flexible and accurate in handling large data sets. The spatial uncertainties in the form of eigenvalues in the direction of the eigenvectors are analyzed from the error covariance matrices of the estimated parameters.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002