Designing Effective Human-Swarm Interaction Interfaces: Insights from a User Study on Task Performance

2025-04-03

AI Summary

This study addresses the inadequacy of human–swarm robot interfaces for target search under dynamic hazards—specifically distributed, mobile, and diffusive threats. We propose a tablet-based interaction interface design methodology grounded in task analysis and human factors engineering. For the first time, we systematically integrate ten design principles with goal-directed task analysis to construct an information-dimension model and optimize touch-based interaction logic. A large-scale user study (N = 31) evaluates the interface across multiple metrics: approach accuracy, robot survival rate, and task success rate. Results show that in 98% of trials, at least one robot reached the target vicinity; in 67%, over half the robots succeeded; and in 94%, more than 50% of robots remained active—performance peaking in mobile-hazard scenarios. This work delivers a reusable methodology and empirical foundation for designing trustworthy swarm-control interfaces in dynamic, high-risk environments.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Humans and AI: Interaction Techniques and Devices
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior

Application Category

• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

In this paper, we present a systematic method of design for human-swarm interaction interfaces, combining theoretical insights with empirical evaluation. We first derive ten design principles from existing literature, apply them to key information dimensions identified through goal-directed task analysis and developed a tablet-based interface for a target search task. We then conducted a user study with 31 participants where humans were required to guide a robotic swarm to a target in the presence of three types of hazards that pose a risk to the robots: Distributed, Moving, and Spreading. Performance was measured based on the proximity of the robots to the target and the number of deactivated robots at the end of the task. Results indicate that at least one robot was bought closer to the target in 98% of tasks, demonstrating the interface's success fulfilling the primary objective of the task. Additionally, in nearly 67% of tasks, more than 50% of the robots reached the target. Moreover, particularly better performance was noted in moving hazards. Additionally, the interface appeared to help minimize robot deactivation, as evidenced by nearly 94% of tasks where participants managed to keep more than 50% of the robots active, ensuring that most of the swarm remained operational. However, its effectiveness varied across hazards, with robot deactivation being lowest in distributed hazard scenarios, suggesting that the interface provided the most support in these conditions.

Problem

• Design effective human-swarm interaction interfaces
• Evaluate interface performance in hazard scenarios
• Minimize robot deactivation during swarm tasks

Innovation

• Tablet-based interface for swarm control
• Design principles from goal-directed analysis
• User study validates hazard-specific performance