Multi-objective sensor planning for efficient and accurate object reconstruction

Enrique Dunn, Gustavo Olague

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

17 Scopus citations

Abstract

A novel approach for sensor planning, which incorporates multi-objective optimization principals into the autonomous design of sensing strategies, is presented. The study addresses planning the behavior of an automated 3D inspection system, consisting of a manipulator robot in an Eye-on-Hand configuration. Task planning in this context is stated as a constrained multi-objective optimization problem, where reconstruction accuracy and robot motion efficiency are the criteria to optimize. An approach based on evolutionary computation is developed and experimental results shown. The obtained convex Pareto front of solutions confirms the conflict among objectives in our planning.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsGunther R. Raidl, Stefano Cagnoni, Jurgen Branke, David W. Corne, Rolf Drechsler, Yaochu Jin, Colin G. Johnson, Penousal Machado, Elena Marchiori, Franz Rothlauf, George D. Smith, Giovanni Squillero
Pages312-321
Number of pages10
ISBN (Electronic)9783540213789
DOIs
StatePublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3005
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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