Analyzing the effect of landmark vectors in homing navigation

Seung Eun Yu, Changmin Lee, Dae Eun Kim

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

The development of an autonomous navigating robot is a challenging task. Motivated by the performance of insects successfully returning to the nest, researchers have studied bio-inspired navigation algorithms for their potential use in mobile robots. In this paper, we analyze landmark-based approaches, especially Distance Estimated Landmark Vector (DELV), Average Correctional Vector and Average Landmark Vector methods, that use landmark vectors for visible environmental landmarks. We evaluated the homing performance of various landmark vector methods with surrounding landmarks under occlusion and found that the occluded or missing landmarks have a significant influence on the performance. We also developed a landmark vector algorithm with a visual compass that uses only retinal images without a reference compass. From our experimental results, we conclude that the DELV shows robust homing navigation performance with missing or occluded landmarks among landmark vector methods.

Original languageEnglish
Pages (from-to)337-359
Number of pages23
JournalAdaptive Behavior
Volume20
Issue number5
DOIs
Publication statusPublished - 2012 Oct 1

All Science Journal Classification (ASJC) codes

  • Experimental and Cognitive Psychology
  • Behavioral Neuroscience

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