Literature DB >> 33352943

The AMIRO Social Robotics Framework: Deployment and Evaluation on the Pepper Robot.

Alexandra Ștefania Ghiță1, Alexandru Florin Gavril1, Mihai Nan1, Bilal Hoteit1, Imad Alex Awada1, Alexandru Sorici1, Irina Georgiana Mocanu1, Adina Magda Florea1.   

Abstract

Recent studies in social robotics show that it can provide economic efficiency and growth in domains such as retail, entertainment, and active and assisted living (AAL). Recent work also highlights that users have the expectation of affordable social robotics platforms, providing focused and specific assistance in a robust manner. In this paper, we present the AMIRO social robotics framework, designed in a modular and robust way for assistive care scenarios. The framework includes robotic services for navigation, person detection and recognition, multi-lingual natural language interaction and dialogue management, as well as activity recognition and general behavior composition. We present AMIRO platform independent implementation based on a Robot Operating System (ROS). We focus on quantitative evaluations of each functionality module, providing discussions on their performance in different settings and the possible improvements. We showcase the deployment of the AMIRO framework on a popular social robotics platform-the Pepper robot-and present the experience of developing a complex user interaction scenario, employing all available functionality modules within AMIRO.

Keywords:  active and assisted living; activity recognition; natural language processing; robotic sensing; social robots; voice commands

Year:  2020        PMID: 33352943      PMCID: PMC7766942          DOI: 10.3390/s20247271

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  2 in total

1.  The Social Robot in Rehabilitation and Assistance: What Is the Future?

Authors:  Daniele Giansanti
Journal:  Healthcare (Basel)       Date:  2021-02-25

2.  Real-Time People Re-Identification and Tracking for Autonomous Platforms Using a Trajectory Prediction-Based Approach.

Authors:  Alexandra Ștefania Ghiță; Adina Magda Florea
Journal:  Sensors (Basel)       Date:  2022-08-05       Impact factor: 3.847

  2 in total

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