Sensing planning to optimize work object location measurements in intelligent robotics

Author

Sallinen, Mikko ; Heikkila, Tapio

Author_Institution

VTT Electron., Oulu, Finland

fYear

2005

fDate

27-30 June 2005

Firstpage

225

Lastpage

230

Abstract

This paper presents a method for planning the sensing features when the geometrical representation of the target object is known. The presented method is a synthesis -form and can be used in several measurement applications in robotics. Sensing planning is an important issue when the measurement data is sparse, includes a lot of noise or there are tight time-requirements. The criteria for selecting the measurement locations and orientations is a posteriori error covariance matrix of the parameters to be estimated. The presented approach is verified by simulation tests in the case of work object location.

Keywords

computational geometry; covariance matrices; feature extraction; intelligent robots; object detection; optimal control; parameter estimation; path planning; robot vision; covariance matrix; geometrical representation; intelligent robotics; pose estimation; sensing planning; spatial uncertainty; work object location measurements; Covariance matrix; Intelligent robots; Jacobian matrices; Modeling; Optical distortion; Optical sensors; Parameter estimation; Robot kinematics; Robot sensing systems; Sensor systems; Sensing planning; pose estimation; spatial uncertainties;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence in Robotics and Automation, 2005. CIRA 2005. Proceedings. 2005 IEEE International Symposium on

Print_ISBN

0-7803-9355-4

Type

conf

DOI

10.1109/CIRA.2005.1554281

Filename

1554281