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Personal assistant robot using reinforcement learning: DARWIN-OP2 as a case study

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Abstract

The use of robots as personal assistants has gained significant interest in recent years. In this research, our motivation is to employ a robot as a personal assistant to optimize the office ergonomics for students. Our personal assistant system consists of DARWIN-OP2 robot, reinforcement algorithm, ROS, communication with robot (using text to speech and speech to text capabilities), and bad posture detection. We conducted a case study on the personal assistant system. The robot receives feedback from student subjects through verbal chatting. Then, the robot executes some tasks such as performing actions or suggesting verbal advice’s to improve the student’s ergonomics. The study included a user evaluation of the robot’s performance, which involved a group of 31 student participants using the robot for a certain period of time. The results show that the DARWIN-OP2 robot is able to effectively and correctly provide valuable health exercises that relieved users’ pains. Additionally, student subjects reported high levels of satisfaction with the robot’s performance and perceived the robot as a helpful personal assistant as it helped in improving their ergonomics. In particular, evaluations of the system, using the group of 31 students, show the system scores 7.7 (out of 10) in speech recognition; 9.7 in health advice’s pain relief; and 9 in users’ opinion on using DARWIN-OP2 as a personal assistant.

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Notes

  1. The maximum number of steps is set to 12, which corresponds to the number of actions in the environment. This is to ensure that each action taken in a given state by the agent is unique and no actions are repeated within the same episode.

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Acknowledgements

We would like to express our sincere gratitude to AlHurriyah Physiotherapy Center located in Amman, Jordan, for their invaluable contribution to our research. Specifically, we would like to extend our thanks to Physiotherapist Hadeel Yousef for providing expert advice on the optimal actions and physiotherapy exercises that could be incorporated into our robotic platform. These recommendations have been utilized in the learning process of our robotic platform and have mitigated pain experienced by human subjects during interactions with the robot. Without the support and guidance from AlHurriyah Physiotherapy Center, this research would not have been possible. We are truly grateful for their contributions.

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Authors and Affiliations

  1. Department of Computer Engineering, Faculty of Engineering, The Hashemite University, P.O. Box 330127, Zarqa, 13133, Jordan

    Khalil M. Ahmad Yousef, Bassam J. Mohd, Omar Barham, Ahmad Al-Najjar, Mohammad Abu-Diab & Anas AlMajali

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  1. Khalil M. Ahmad Yousef
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  2. Bassam J. Mohd
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  3. Omar Barham
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  4. Ahmad Al-Najjar
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  5. Mohammad Abu-Diab
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Correspondence to Khalil M. Ahmad Yousef.

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Ahmad Yousef, K.M., Mohd, B.J., Barham, O. et al. Personal assistant robot using reinforcement learning: DARWIN-OP2 as a case study. Intel Serv Robotics 17, 815–831 (2024). https://doi.org/10.1007/s11370-024-00540-7

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  • DOI: https://doi.org/10.1007/s11370-024-00540-7

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