Human-Swarm Interaction: Theory, Practice, and Real-World Deployments

Robot swarms, much like natural swarms such as ants and bees, consist of many independent autonomous agents working together to achieve a common task. Due to their decentralized nature, robot swarms are inherently scalable and robust to individual failures. They are capable of covering large areas or engaging with many people simultaneously. These qualities have enabled swarms to prove useful in diverse domains from providing wide-area coverage with firefighting drones to engaging groups of children in STEM education.

As robot swarms move beyond controlled laboratory settings and into real-world applications, human-swarm interaction (HSI) becomes a critical factor for their effective deployment. Successful deployments require designing interactions for communication between humans and swarms, coordinating robotic agents to respond meaningfully to human input, and ensuring feedback mechanisms that maintain smooth, intuitive engagement. Learning methods could further be used to enable the swarm to continuously adapt and learn from human interaction. The specific methods used will depend on the hardware design, sensing and communication capabilities, and the application domain.

The goal of this Research Topic is to present and synthesize the diverse methods, approaches, and applications of human-swarm interaction across domains. By gathering contributions from across the field, we aim to provide researchers with both theoretical insights and practical tools for designing and programming swarms that can effectively collaborate with or be operated by humans. We hope this Research Topic will serve as a valuable resource for researchers who want to accumulate knowledge on human-swarm interaction and for practitioners seeking ways to design and deploy swarms in the real world

We encourage submissions on (but not limited to) the following topics:
· Control strategies linking human input to multi-agent behaviors
· Evaluation metrics for assessing the quality, efficiency, and effectiveness of human-swarm interactions
· Methodologies for testing usability, scalability, and robustness of multi-agent systems
· Learning approaches for adaptive and personalized swarm behavior
· Foundation models that enable multi-agent systems to learn and adapt in dynamic environments
· User studies with multi-agent systems in both controlled and real-world settings
· Real-world deployments of robot swarms across diverse domains
· Human-centered swarm design to facilitate intuitive, practical, and effective use
· Trustworthy system design to ensure safe and reliable operation in human-centric contexts
· Interface design for seamless, natural, and engaging human-swarm interactions
· Human-swarm interaction modalities including hand gestures, voice, and multimodal interfaces
· Cognitive workload and human factors of using and interacting with swarms
· Ethical, legal, and social implications of deploying swarms in real-world applications

Topic Coordinator Merihan Alhafnawi receives financial support for research from Amazon. The other Topic Editors report no competing interests related to this Research Topic.