Design Space of Human Swarm Interactions

Exploring Novel Interaction Paradigms for Human-Swarm Collaboration

Project Overview

This research project explores the design space of interaction paradigms between humans and robotic swarms. We focus on developing intuitive and effective ways for humans to collaborate with large groups of autonomous robots, addressing challenges in visualization, control mechanisms, and real-time feedback systems.

Technologies Used:
Unity3D ROS Python VR/AR C# Machine Learning

Quick Links

Source Code Demo Video Research Paper Gallery

Key Features

Immersive Interaction

Virtual and augmented reality interfaces for intuitive swarm control and visualization, enabling natural gestures and spatial awareness.

Swarm Intelligence

Advanced algorithms for coordinated behavior and emergent intelligence in robot swarms, with real-time adaptation to human input.

Visual Analytics

Real-time visualization of swarm behavior, state, and performance metrics, supporting informed decision-making.

Adaptive Control

Machine learning-based systems that adapt to user preferences and optimize human-swarm collaboration over time.

Research Goals

  • 1. Interaction Design

    Develop and evaluate novel interaction techniques for controlling and monitoring robot swarms in various application contexts.

  • 2. Visualization Methods

    Create effective visualization techniques for understanding swarm behavior, state, and intentions in real-time.

  • 3. Human Factors

    Study cognitive load, situational awareness, and user experience in human-swarm interaction scenarios.

  • 4. Applications

    Explore practical applications in search and rescue, environmental monitoring, and industrial automation.

Design Space Visualization

This interactive visualization represents the six primary dimensions of human-swarm interactions: Application Scenario, Tasks, Autonomy, Behaviors, Interaction, and Visualization. The connecting lines show different interaction paradigms across these dimensions. Hover over elements to explore relationships and get detailed descriptions.

Example Paradigms:
Emergency Response Search and rescue operations with real-time 3D visualization
Warehouse Automation Collaborative material handling with gesture control
Environmental Monitoring Autonomous data collection with strategic oversight
Interactive Performance Dynamic swarm performances with voice commands

Project Gallery

Swarm Interface

VR Interface for Swarm Control

Swarm Visualization

Real-time Swarm Visualization

Swarm Demo

Physical Robot Swarm Demo

Team & Contact

For more information about this project or collaboration opportunities, please contact:

Email: contact@example.com

GitHub: Project Repository