Dances with Drones: Spatial Matching and Perceived Agency in Improvised Movements with Drone and Human Partners

Title of the Paper

Dances with Drones: Spatial Matching and Perceived Agency in Improvised Movements with Drone and Human Partners

Paper Information

• Domain: Human-Computer Interaction and Creative Dance
• Keywords: Improvised Dance, Micro Aerial Vehicles, Human-Computer Interaction, Spatial Matching, Perceived Agency, Dance Education, Technological Art, Multimodal Interaction

Research Background and Issues

• Identified Problems or Challenges:

  • As drones increasingly integrate into human activities, such as light shows, understanding the potential and impact of human-drone collaborative performances has become a research focus.
  • Humans exhibit different behaviors when performing alone versus with collaborators, but how to incorporate non-human collaborators, including drones, remains underexplored.
  • Current research lacks a detailed understanding of human-drone interaction in improvised dance contexts and how drones influence dancers' behavior and perception.

• Significance of the Issue:

  • Integrating technology (e.g., drones) into dance can inspire new art forms and provide novel technological applications, advancing the field of human-computer interaction.
  • Exploring human-drone collaboration in improvised dance offers new insights for the integration of art, education, and technology.

• Research Motivation and Related Work:

  • Drones have gradually appeared in performing arts, but there is limited in-depth research on enhancing collaboration and perception between dancers and drones.
  • Investigating how drones influence dance creativity and performance by combining spatial dynamics and multimodal features (e.g., visual, auditory) will drive new directions in improvisational dance and interactive technology research.

Proposed Solutions

• Proposed Methods and Solutions:

  1. Developed a dance system centered on micro drones to support improvised solo and collaborative dances with drones or human partners.
  2. Predefined four drone trajectory stages, including circular motion, forward-backward movement, vertical movement, and lateral movement, to observe dancers' responses to different spatial movement patterns.

• Innovations:

  • Introduced pre-programmed trajectory drones into improvised dance for the first time to study their impact on dancers' spatial exploration, movement inspiration, and perceived agency.
  • Adopted a dual-modal data collection approach (interviews and computer vision analysis) to quantify the interaction between dancers and drones.

• Implementation Steps and Key Technologies:

  1. Participant Experiment:
     • Recruited 12 dancers with varying levels of experience to conduct solo and duo dance experiments interacting with drones.
  2. Data Collection:
     • Semi-structured interviews and questionnaires explored dancers' perceptions of drones and space.
     • 3D pose estimation and video coding techniques analyzed dancers' body movements.
  3. Data Analysis:
     • Quantitatively compared dancers' behaviors in single-drone versus dual-drone scenarios.
     • Conducted coding and thematic analysis to uncover dancers' subjective perceptions of drone characteristics.

Research Findings

• Specific Findings:

  1. Human-Drone Relationship: Dancers often positioned themselves as followers rather than equal collaborators with drones.
  2. Spatiotemporal Interaction: As the number of drones increased, dancers' spatial behaviors became more complex, favoring lower-position and evasive movements.
  3. Multimodal Experience: Drone-generated sounds and speed were key parameters for dancers to judge drone dynamics, while also inspiring dance creativity.

• Comparison with Existing Solutions and Advantages:

  • This study provided a multidimensional analysis of dance experiences from the perspectives of emotional perception and spatial interaction, enriching design theories for human-robot collaboration.
  • It offered specific design guidelines for introducing non-humanoid robots into performing arts, addressing gaps in research on technology-driven improvisational dance.

• Experimental or Evaluation Results:

  1. In single-drone scenarios, dancers reported significantly higher scores for connection and comfort compared to dual-drone scenarios.
  2. In dual-drone scenarios, dancers exhibited greater motivation for spatial exploration, despite increased complexity.
  3. Dancers' perceptions underwent a dynamic shift from "avoidance-fear" to "approach-exploration."

• Limitations and Future Directions:

  • Limitations:
    1. Drone trajectories were predefined, lacking real-time interaction.
    2. The study primarily involved social dancers, with limited exploration of other dance styles and stage environments.
    3. Experiments were conducted mainly in laboratory settings, with insufficient validation in live stage contexts.
  • Future Directions:
    1. Explore more complex drone trajectories and real-time feedback mechanisms to enhance interactivity.
    2. Expand to more dance styles and test in actual stage scenarios.
    3. Investigate how sound, lighting, and multi-drone collaboration can further enrich artistic presentations.