Sensing planning to optimize work object location measurements in intelligent robotics

Mikko Sallinen; Tapio Heikkilä

doi:10.1109/CIRA.2005.1554281

Sensing planning to optimize work object location measurements in intelligent robotics

Mikko Sallinen, Tapio Heikkilä

VTT Technical Research Centre of Finland

University of Oulu

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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.

Original language	English
Title of host publication	2005 International Symposium on Computational Intelligence in Robotics and Automation
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	225-230
ISBN (Print)	978-0-7803-9355-4
DOIs	https://doi.org/10.1109/CIRA.2005.1554281
Publication status	Published - 2005
MoE publication type	A4 Article in a conference publication
Event	IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2005 - Espoo, Finland Duration: 27 Jun 2005 → 30 Jun 2005

Conference

Conference	IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2005
Country/Territory	Finland
City	Espoo
Period	27/06/05 → 30/06/05

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10.1109/CIRA.2005.1554281

Cite this

@inproceedings{6dde85808d064fe998121801c3a89ba7,

title = "Sensing planning to optimize work object location measurements in intelligent robotics",

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.",

author = "Mikko Sallinen and Tapio Heikkil{\"a}",

year = "2005",

doi = "10.1109/CIRA.2005.1554281",

language = "English",

isbn = "978-0-7803-9355-4",

pages = "225--230",

booktitle = "2005 International Symposium on Computational Intelligence in Robotics and Automation",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

address = "United States",

note = "IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2005 ; Conference date: 27-06-2005 Through 30-06-2005",

}

Sallinen, M & Heikkilä, T 2005, Sensing planning to optimize work object location measurements in intelligent robotics. in 2005 International Symposium on Computational Intelligence in Robotics and Automation. IEEE Institute of Electrical and Electronic Engineers, pp. 225-230, IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2005, Espoo, Finland, 27/06/05. https://doi.org/10.1109/CIRA.2005.1554281

Sensing planning to optimize work object location measurements in intelligent robotics. / Sallinen, Mikko; Heikkilä, Tapio.
2005 International Symposium on Computational Intelligence in Robotics and Automation. IEEE Institute of Electrical and Electronic Engineers, 2005. p. 225-230.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Sensing planning to optimize work object location measurements in intelligent robotics

AU - Sallinen, Mikko

AU - Heikkilä, Tapio

PY - 2005

Y1 - 2005

N2 - 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.

AB - 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.

U2 - 10.1109/CIRA.2005.1554281

DO - 10.1109/CIRA.2005.1554281

M3 - Conference article in proceedings

SN - 978-0-7803-9355-4

SP - 225

EP - 230

BT - 2005 International Symposium on Computational Intelligence in Robotics and Automation

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2005

Y2 - 27 June 2005 through 30 June 2005

ER -

Sensing planning to optimize work object location measurements in intelligent robotics

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