Intention Indication for Human Aware Robot Navigation

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Abstract

Robots are gradually making their ways from factory floors to our everyday living environments. Mobile robots are becoming more ubiquitous in many domains: logistics, entertainment, security, healthcare, etc. For robots to enter the everyday human environment they need to understand us and make themselves understood. In other words, they need to make their intentions clear to people. This is especially important regarding intentions of movement: when robots are starting, stopping, turning left, right, etc. In this study we explore three different ways for a wheeled mobile robot to communicate its intentions on which way it will go at a hallway intersection: one analogous to automotive signaling, another based on movement gesture and as a third option a novel light signal. We recorded videos of the robot approaching an intersection with the given methods and asked subjects via a survey to predict the robot’s actions. The car analogy and turn gesture performed adequately, while the novel light signal less so. In the following we describe the setup and outcomes of this study, as well as give suggestions on how mobile robots should signal in indoor spaces based on our findings.
Original languageEnglish
Title of host publicationProceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: HUCAPP
EditorsManuela Chessa, Alexis Paljic, Jose Braz
Volume2
PublisherSCITEPRESS Digital Library
Publication date2020
Pages64-74
ISBN (Print)978-989-758-402-2
ISBN (Electronic)9789897584022
DOIs
Publication statusPublished - 2020
Event15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Valletta, Malta
Duration: 27. Feb 202029. Feb 2020
Conference number: 15

Conference

Conference15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Number15
CountryMalta
CityValletta
Period27/02/202029/02/2020

Keywords

  • Human aware navigation
  • Intention
  • Mobile robots

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