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Real Robot Dance Challenge: Exploring live and online dance challenge videos for robot movement

Published: 27 June 2024 Publication History

Abstract

This paper describes a proposed robotic artwork for the MOCO 2024 conference. Real Robot Dance Challenge is a human-robot art installation that investigates both live human-robot interactions as well as human movement embedded in online videos as sources for the robot's movement. Dance is extremely challenging for a robot in terms of movement goals. Compared to typical industrial robot approaches, actions may have a comparative excess expenditure of energy, and style and expressivity becoming more important than accuracy and control. This work draws on the popular trend of dance challenges as seen on platforms such as Tik Tok [1]. The short format dances, often 10 – 30 seconds long, are choreographed with the intention of showcasing skills as well as challenging others to reinterpret the dance, often done with individual stylistic changes. RRDC challenges the robot to reinterpret the movement of human movers interacting live as well as dances contained in online videos. The artwork leverages the unity game engine as a mediating platform for the robot to access human movement and repurpose it for its own body. This allows the robot's movement to be procured from multiple sources. The unity environment can also be used to connect robots of different morphologies to the movement sources enabling flexibility in the engagement between human and robot. The robot moves beyond the control of programmed actions, able to respond with interpretations of the movement offered to it.

References

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Klug, D., "It took me almost 30 minutes to practice this". Performance and Production Practices in Dance Challenge Videos on TikTok. 2020.
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LaViers, A., Choreogarphic Abstractions for Style-Based Robotic Motion, in School of Electrical and Computer Engineering. 2013, Georgia Institute of Technology. p. 102.
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Rogel, A., RoboGroove: Creating Fluid Motion for Dancing Robotic Arms, in Proceedings of the 8th International Conference on Movement and Computing. 2022, Association for Computing Machinery: Chicago, IL, USA. p. Article 7.
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Saviano, G., A. Villani, and D. Prattichizzo. A PCA-based Method to Map Aesthetic Movements from Dancer to Robotic Arm. in 2023 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO). 2023.
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Stanton, C., A. Bogdanovych, and E. Ratanasena. Teleoperation of a humanoid robot using full-body motion capture, example movements, and machine learning. in Proceedings of Australasian Conference on Robotics and Automation, . 2012. Victoria University of Wellington, New Zealand.
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Wang, C., Intuitive and Versatile Full-body Teleoperation of A Humanoid Robot. 2021. IEEE.
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Vongchumyen, C., Teleoperation of Humanoid Robot by Motion Capturing Using KINECT. 2018. IEEE.
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Masumori, A., N. Maruyama, and T. Ikegami, Personogenesis Through Imitating Human Behavior in a Humanoid Robot “Alter3”. Frontiers in Robotics and AI, 2021. 7.
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Google. Mediapipe. 2023; Available from: https://github.com/google/mediapipe.
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Kennedy, M., ‘If the rise of the TikTok dance and e-girl aesthetic has taught us anything, it's that teenage girls rule the internet right now’: TikTok celebrity, girls and the Coronavirus crisis. European Journal of Cultural Studies, 2020. 23(6): p. 1069-1076.

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Published In

cover image ACM Other conferences
MOCO '24: Proceedings of the 9th International Conference on Movement and Computing
May 2024
245 pages
ISBN:9798400709944
DOI:10.1145/3658852
This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 June 2024

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Author Tags

  1. AI
  2. Human Robot Interaction
  3. Robot Dance
  4. Robot Dance Challenge
  5. Robot Installation
  6. Unity

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  • Research-article
  • Research
  • Refereed limited

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MOCO '24

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MOCO '24 Paper Acceptance Rate 35 of 75 submissions, 47%;
Overall Acceptance Rate 85 of 185 submissions, 46%

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