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Perirobot Space Representation for HRI: Measuring and Designing Collaborative Workspace Coverage by Diverse Sensors

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00367323" target="_blank" >RIV/68407700:21230/23:00367323 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1109/IROS55552.2023.10341829" target="_blank" >https://doi.org/10.1109/IROS55552.2023.10341829</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/IROS55552.2023.10341829" target="_blank" >10.1109/IROS55552.2023.10341829</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Perirobot Space Representation for HRI: Measuring and Designing Collaborative Workspace Coverage by Diverse Sensors

  • Original language description

    Two regimes permitting safe physical human-robot interaction, speed and separation monitoring and safety-rated monitored stop, depend on reliable perception of the space surrounding the robot. This can be accomplished by visual sensors (like cameras, RGB-D cameras, LIDARs), proximity sensors, or dedicated devices used in industrial settings like pads that are activated by the presence of the operator. The deployment of a particular solution is often ad hoc and no unified representation of the interaction space or its coverage by the different sensors exists. In this work, we make first steps in this direction by defining the spaces to be monitored, representing all sensor data as information about occupancy and using occupancy-based metrics to calculate how a particular sensor covers the workspace. We demonstrate our approach in two sensor-placement experiments in three static scenes and one experiment in a dynamic scene. The occupancy representation allow the comparison of the effectiveness of various sensor setups. Therefore, this approach can serve as a prototyping tool to establish the sensor setup that provides the most efficient coverage for the given metrics and sensor representations.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20204 - Robotics and automatic control

Result continuities

  • Project

    <a href="/en/project/GX20-24186X" target="_blank" >GX20-24186X: Whole-body awareness for safe and natural interaction: from brains to collaborative robots</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

  • ISBN

    978-1-6654-9190-7

  • ISSN

    2153-0858

  • e-ISSN

    2153-0866

  • Number of pages

    8

  • Pages from-to

    5958-5965

  • Publisher name

    IEEE

  • Place of publication

    Piscataway

  • Event location

    Detroit, MA

  • Event date

    Oct 1, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001136907800090