RemoteLab: Virtual Reality Remote study Tool Kit

Document Title

RemoteLab: A VR Remote Study Toolkit

Document Information

• Topic Area: Development of remote virtual reality (VR) user research tools
• Keywords: Virtual reality, user research, Unity, toolkit, remote user study, synchronized experiments, questionnaire tools, data recording and playback, research development

Research Background and Issues

• Identified Problems/Challenges:
  • Traditional user studies conducted in physical labs require participants to be present at specific locations, limiting participant diversity and numbers.
  • Social distancing restrictions during the COVID-19 pandemic made in-person experiments difficult to conduct.
  • While remote user studies show potential, setting up experimental software is often technically complex, especially for VR-based experiments.
• Significance:
  • VR research requires specialized hardware (e.g., head-mounted displays (HMDs), handheld controllers), which cannot fully address diverse research needs solely in lab environments.
  • The widespread availability of consumer-grade VR hardware creates technical possibilities for remote user studies, but efficient and user-friendly tool support is lacking.
• Research Motivation and Related Work:
  • Existing studies indicate that remote VR experiments can yield reliable data, but compared to lab-based research, remote implementation still faces challenges in standardization and hardware operation guidance.
  • Previous remote experimental tools (e.g., experiments based on social VR platforms) show significant limitations in operational independence and comprehensive data collection.

Solution

• Proposed Method or Solution:
  • RemoteLab is an open-source toolkit based on Unity, designed to support synchronized remote VR user experiments.
• Innovative Features:
  1. Supports synchronization of experimental states across multiple sites.
  2. Records data from various media sources (e.g., user behavior, audio, and video).
  3. Provides playback functionality after experiments for detailed analysis.
  4. Designed with a modular architecture, enabling users to customize and extend functionalities.
• Implementation Steps and Key Technologies:
  1. Experiment Control and Synchronization: Utilizes Photon Unity Networking (PUN 2) to enable shared virtual environments among remote users.
  2. Streamlined Experiment Workflow: Integrates questionnaire functionality within VR, reducing the complexity of switching between scenes.
  3. Ease of Use Design: Offers pre-built modules (e.g., standardized questionnaire templates) and supports drag-and-drop operations.
  4. Data Recording and Compression: Stores data locally and optimizes transmission efficiency using Google Protocol Buffers and compression algorithms.
  5. Playback and Analysis: Employs Unity Editor's timeline slider functionality to synchronize playback of VR scenes with video/audio data.

Research Outcomes

• Specific Achievements:
  1. Developed and demonstrated the functionalities of the RemoteLab toolkit, including experiment control, data collection and synchronization, and experiment result playback.
  2. Provided a standardized set of questionnaires and experimental interfaces, enabling researchers to quickly design and conduct experiments.
  3. Successfully implemented multi-user synchronized experiments and data analysis capabilities.
• Advantages Over Existing Solutions:
  • Compared to traditional labs: Covers a broader participant pool, eliminating geographical constraints.
  • Compared to other remote research tools: Enhances real-time experimental control, comprehensive data collection, and smooth experimental workflows.
• Experimental or Evaluation Results:
  • The toolkit underwent internal testing and informal feedback from external scholars; researchers found it simple and practical to use.
  • High data recording efficiency, with compressed text record files averaging 3MB for approximately 1 minute of scene usage.
• Limitations and Future Directions:
  • Currently relies on PUN 2 for synchronization, which may impose technical burdens on some users.
  • Data transmission efficiency requires further optimization, especially in low-bandwidth environments.
  • Lacks support for free-text responses in questionnaires.
  • Future improvements include introducing more advanced compression and transmission algorithms, supporting depth sensor data collection, and expanding to augmented reality (AR) and other display platforms.