Daniel R. Little

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About

Daniel R. Little is a leading researcher in human-robot interaction and autonomous systems, with a particular focus on trust dynamics in swarm robotics. His work addresses the critical challenge of how human operators develop and maintain trust when commanding autonomous robotic swarms, especially in high-stakes environments. Little's most-cited paper, "Asymmetrical Trust Modeling for Human-Robot Swarm Interactions" (2025), introduces a novel framework that captures the imbalance between human trust in automation and the swarm's reliability—a key insight for designing safer, more effective human-swarm teams. By modeling trust as an asymmetrical, dynamic process, his research provides practical pathways for improving collaboration between humans and increasingly autonomous systems. Though early in its citation trajectory, this work has already garnered attention for its timely relevance as swarms move from laboratory settings into real-world applications like search-and-rescue, surveillance, and disaster response. Little's contributions are shaping how engineers and psychologists approach the design of transparent, trustworthy autonomous systems, making him a rising voice in the intersection of robotics, cognitive science, and human factors engineering.