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Open Access NAO (OAN): a ROS2-based software framework for HRI applications with the NAO robot

Antonio Bono, Kenji Brameld, Luigi D'Alfonso, Giuseppe Fedele

TL;DR

A new software framework for HRI experimentation with the sixth version of the common NAO robot produced by the United Robotics Group, taking advantage of the ability to run ROS2 onboard on the NAO to develop a framework independent of the APIs provided by the manufacturer.

Abstract

This paper presents a new software framework for HRI experimentation with the sixth version of the common NAO robot produced by the United Robotics Group. Embracing the common demand of researchers for better performance and new features for NAO, the authors took advantage of the ability to run ROS2 onboard on the NAO to develop a framework independent of the APIs provided by the manufacturer. Such a system provides NAO with not only the basic skills of a humanoid robot such as walking and reproducing movements of interest but also features often used in HRI such as: speech recognition/synthesis, face and object detention, and the use of Generative Pre-trained Transformer (GPT) models for conversation. The developed code is therefore configured as a ready-to-use but also highly expandable and improvable tool thanks to the possibilities provided by the ROS community.

Open Access NAO (OAN): a ROS2-based software framework for HRI applications with the NAO robot

TL;DR

A new software framework for HRI experimentation with the sixth version of the common NAO robot produced by the United Robotics Group, taking advantage of the ability to run ROS2 onboard on the NAO to develop a framework independent of the APIs provided by the manufacturer.

Abstract

This paper presents a new software framework for HRI experimentation with the sixth version of the common NAO robot produced by the United Robotics Group. Embracing the common demand of researchers for better performance and new features for NAO, the authors took advantage of the ability to run ROS2 onboard on the NAO to develop a framework independent of the APIs provided by the manufacturer. Such a system provides NAO with not only the basic skills of a humanoid robot such as walking and reproducing movements of interest but also features often used in HRI such as: speech recognition/synthesis, face and object detention, and the use of Generative Pre-trained Transformer (GPT) models for conversation. The developed code is therefore configured as a ready-to-use but also highly expandable and improvable tool thanks to the possibilities provided by the ROS community.
Paper Structure (18 sections, 3 figures)

This paper contains 18 sections, 3 figures.

Table of Contents

  1. Introduction
  2. Background and related works
  3. The OAN software framework
  4. The underlying operating system
  5. The framework components
  6. NAO_LoLA
  7. NAO_POS
  8. WALK
  9. NAO_LED
  10. ROS community modules
  11. The related simulator
  12. The Human NAO Interaction package
  13. Teach by demonstration
  14. Face/object detection and tracking
  15. Speech recognition and synthesis
  16. ...and 3 more sections

Figures (3)

  • Figure 1: A graph describing the data flow among different parts of the OAN framework. Ellipses and parallelograms are modules and packages, respectively. Dashed lines shows parts developed by the ROS community.
  • Figure 2: A screenshot from the Webots simulator using the LoLA controller.
  • Figure 3: NAO chatting with a user using the OAN framework. The robot is focusing on the user face and plays a gesture while speaking.