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Detection and Tracking of Moving Obstacles (DATMO): A Review

Published online by Cambridge University Press:  12 July 2019

Ángel Llamazares ,
Eduardo J. Molinos  and
Manuel Ocaña Open the ORCID record for Manuel Ocaña [Opens in a new window]
Ángel Llamazares*
Affiliation:
Department of Electronics, University of Alcalá, Alcalá de Henares, Spain
Eduardo J. Molinos
Affiliation:
Institut für Mess - und Regelungstechnik, Karlsruhe Institut fur Technologie, Karlsruhe, Germany Email: eduardo.molinos@kit.edu
Manuel Ocaña
Affiliation:
Department of Electronics, University of Alcalá, Alcalá de Henares, Spain Email: mocana@depeca.uah.es
*
*Corresponding author. E-mail: angel.llamazares@uah.es
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Summary

Working with mobile robots, prior to execute the local planning stage, they must know the environment where they are moving. For that reason the perception and mapping stages must be performed previously. This paper presents a survey in the state of the art in detection and tracking of moving obstacles (DATMO). The aim of what follows is to provide an overview of the most remarkable methods at each field specially in indoor environments where dynamic obstacles can be potentially more dangerous and unpredictable. We are going to show related DATMO methods organized in three approaches: model-free, model-based and grid-based. In addition, a comparison between them and conclusions will be presented.

Keywords

DATMOGrid-basedModel-freeModel-based

Information

Type
Articles
Information
Robotica , Volume 38 , Issue 5 , May 2020 , pp. 761 - 774
Copyright
© Cambridge University Press 2019

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