Snapshot homing navigation based on edge features

Seungmin Baek, Daeeun Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


The insect has a navigation ability to estimate the direction to their habitat using visual information after finding their food. It is known that many insects including ants can use visual snapshot around them for homing navigation. Inspired by this navigation ability of insect, many navigation algorithms have been suggested. One of the navigation algorithms is the average landmark vector (ALV) algorithm to calculate the direction to the target location relative to the current location. This algorithm is based on the observation of landmarks from visual information. Observing and identifying landmarks in real environment is a challenging problem. For the snapshot model, the feature extraction from the visual image plays an important role. Segmentation or clustering over color pixels may not provide a robust solution to find landmarks in the snapshot model. In this paper, we suggest that a vertical edge features with neighbor pixel colors can be a very efficient and effective solution to identify landmarks. These vertical edge features are not warped by the movement of camera, and they maintain the characteristic for the movement of a robot. We test a new algorithm of detecting these vertical edge features as landmarks and finding the correspondence between those landmarks at the nest and at the current location. As a result, the algorithm easily determines the homing direction.

Original languageEnglish
Title of host publicationFrom Animals to Animats 13 - 13th International Conference on Simulation of Adaptive Behavior, SAB 2014, Proceedings
PublisherSpringer Verlag
Number of pages10
ISBN (Print)9783319088631
Publication statusPublished - 2014
Event13th International Conference on the Simulation of Adaptive Behavior, SAB 2014 - Castellon, Spain
Duration: 2014 Jul 222014 Jul 25

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8575 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other13th International Conference on the Simulation of Adaptive Behavior, SAB 2014

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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