<p>Robots are becoming increasingly popular across various industries, including manufacturing, healthcare, agriculture, and personal services. This growing demand has spurred the development of robots with specialized abilities and applications, improving safety, productivity, and quality of life. This paper focuses on service robots with verbal and visual communication, which play a crucial role in human–robot interaction. We propose a novel method to enhance the accuracy of this communication by combining sound localization and image processing, enabling more natural interactions. Additionally, we aim to improve the service robot’s mobility and interaction by adjusting its rotational speed to match human movement, thus enhancing adaptability and usability in diverse environments. This paper provides an overview of similar research efforts in human–robot interactions, details our proposed methodology, describes human–robot test environments, and presents experimental results, conclusions and implications for future research.</p>

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Multi-modal, multi-step human–robot interaction method for natural interaction of service robots

  • Jargalbaatar Yura,
  • Bat-Erdene Byambasuren,
  • Donghan Kim

摘要

Robots are becoming increasingly popular across various industries, including manufacturing, healthcare, agriculture, and personal services. This growing demand has spurred the development of robots with specialized abilities and applications, improving safety, productivity, and quality of life. This paper focuses on service robots with verbal and visual communication, which play a crucial role in human–robot interaction. We propose a novel method to enhance the accuracy of this communication by combining sound localization and image processing, enabling more natural interactions. Additionally, we aim to improve the service robot’s mobility and interaction by adjusting its rotational speed to match human movement, thus enhancing adaptability and usability in diverse environments. This paper provides an overview of similar research efforts in human–robot interactions, details our proposed methodology, describes human–robot test environments, and presents experimental results, conclusions and implications for future research.