Evolutionary computation for sensor planning: The task distribution plan

Enrique Dunn, Gustave Olague

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Autonomous sensor planning is a problem of interest to scientists in the fields of computer vision, robotics, and photogrammetry. In automated visual tasks, a sensing planner must make complex and critical decisions involving sensor placement and the sensing task specification. This paper addresses the problem of specifying sensing tasks for a multiple manipulator workcell given an optimal sensor placement configuration. The problem is conceptually divided in two different phases: activity assignment and tour planning. To solve such problems, an optimization methodology based on evolutionary computation is developed. Operational limitations originated from the workcell configuration are considered using specialized heuristics as well as a floating-point representation based on the random keys approach. Experiments and performance results are presented.

Original languageEnglish
Pages (from-to)748-756
Number of pages9
JournalEurasip Journal on Applied Signal Processing
Volume2003
Issue number8
DOIs
StatePublished - 1 Jul 2003

Keywords

  • Combinatorial optimization
  • Evolutionary computing
  • Random keys
  • Sensor planning

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