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Collider-based movement detection and control of wearable soft robots for visually augmenting dance performance.

Patrick Twomey1, Vaibhavsingh Varma1, Leslie L Bush2

  • 1Department of Mechanical Engineering, Henry M. Rowan College of Engineering, Rowan University, Glassboro, NJ, United States.

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Summary

A novel collider-based algorithm accurately tracks improvisational dance movements, enabling wearable soft robots to respond dynamically. This technology enhances artistic expression by integrating spontaneous motion with interactive stage effects.

Keywords:
activity recognitioncollidersdanceinertial measurement units (IMUs)movement detectionsoft robotswearable sensors

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Area of Science:

  • Robotics and Human-Computer Interaction
  • Performance Art Technology
  • Biomechanical Motion Analysis

Background:

  • Improvisational dance presents unique motion-tracking challenges due to unpredictable, non-repetitive movements.
  • Existing methods like optical tracking (limb occlusion) and inertial measurement units (complex algorithms, fixed thresholds) have limitations.
  • Machine learning is often unsuitable for improvisational dance due to limited unique training data.

Purpose of the Study:

  • To develop an adaptable and robust motion-tracking algorithm for improvisational dance.
  • To enable real-time control of wearable soft robotic actuators based on dancer movements.
  • To enhance the expressive potential of dance through technology integration.

Main Methods:

  • Introduction of a collider-based movement detection algorithm, modeling colliders as virtual mass-spring-damper systems.
  • Defining colliders in limb-specific planes to capture dynamics in their relative frame, avoiding IMU drift.
  • Implementing a simplified detection scheme using individual dynamic system response variables and a hashing method for high-speed processing.

Main Results:

  • The collider-based algorithm effectively detects complex, improvisational dance movements.
  • Demonstrated control of wearable, origami-based soft actuators (changing size and lighting) in response to detected movements.
  • Experimental validation of the algorithm's robustness and speed for real-time dance applications.

Conclusions:

  • The proposed algorithm offers a robust solution for tracking arbitrary dance motions, overcoming limitations of conventional methods.
  • This technology allows dancers to trigger stage events organically, creating novel aesthetic experiences.
  • The research highlights the potential of integrating advanced robotics and sensing with spontaneous artistic expression to augment performance art.