Sensor fusion techniques are able to increase robustness and accuracy over data provided by isolated sensors. Fusion can be performed at a low level, creating shared data representations from multiple sensory inputs, or at a high level, checking consistency and similarity of objects provided by different sources. These last techniques are more prone to discard perceived objects due to overlapping or partial occlusions, but they are usually simpler, and more scalable. Hence, they are more adequate when data gathering is the key requirement, while safety is not compromised, computational resources may be limited and it is important to easily incorporate new sensors (e.g. monitorization in smart environments or object recognition for social robots). This paper proposes a novel perception integrator module that uses low complexity algorithms to implement fusion, tracking and forgetting mechanisms. Its main characteristics are simplicity, adaptability and scalability. The system has been integrated in a social robot and employed to achieve multimodal object and person recognition. Experimental results show the adequacy of the solution in terms of detection and recognition rates, integrability into the constrained resources of a robot, and adaptability to different sensors, detection priorities and scenarios.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Multimodal Object Recognition Module for Social Robots


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Tardioli, Danilo (Herausgeber:in) / Matellán, Vicente (Herausgeber:in) / Heredia, Guillermo (Herausgeber:in) / Silva, Manuel F. (Herausgeber:in) / Marques, Lino (Herausgeber:in) / Cruces, Alejandro (Autor:in) / Tudela, Alberto (Autor:in) / Romero-Garcés, Adrián (Autor:in) / Bandera, Juan Pedro (Autor:in)

    Kongress:

    Iberian Robotics conference ; 2022 ; Zaragoza, Spain November 23, 2022 - November 25, 2022



    Erscheinungsdatum :

    19.11.2022


    Format / Umfang :

    13 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Modelling Multimodal Dialogues for Social Robots Using Communicative Acts

    Fernández Rodicio, Enrique / Castro González, Álvaro / Alonso Martín, Fernando et al. | BASE | 2020

    Freier Zugriff

    Object-based Place Recognition for Mobile Robots Using Panoramas

    Ribes, Arturo / Ramisa, Arnau / López de Mántaras, Ramón et al. | BASE | 2008

    Freier Zugriff

    Learning to select Object Recognition Methods for Autonomous Mobile Robots

    Bianchi, Reinaldo / Ramisa, Arnau / López de Mántaras, Ramón | BASE | 2008

    Freier Zugriff

    A Tale of Two Object Recognition Methods for Mobile Robots

    Ramisa, Arnau / Vasudevan, Shrihari / Scharamuzza, Davide et al. | BASE | 2008

    Freier Zugriff

    Multi-modal Emotion Recognition for User Adaptation in Social Robots

    Schiffmann, Michael / Thoma, Aniella / Richert, Anja | TIBKAT | 2021