Breelyn Kane

Papers

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About

Breelyn Kane is a pioneering researcher in the field of multi-human/multi-robot teaming, with a primary focus on how human operators can effectively control and coordinate large teams of autonomous robots. Her work centers on understanding the critical interplay between task allocation, automation, and team organization in complex operational domains. Kane’s major contributions include developing a foundational theory for human control of robot teams that examines how control strategies shift across different task allocations, particularly in foraging and Urban Search and Rescue (USAR) scenarios. Her most cited work, “Teams organization and performance in multi-human/multi-robot teams” (34 citations), investigates how automation levels and team structures impact performance when humans supervise robots performing largely independent tasks. In her subsequent study, “Teams for Teams Performance in Multi-Human/Multi-Robot Teams” (11 citations), she further dissects the USAR domain into three critical subtasks—perceptual visual search, teleoperation assistance, and navigation—to analyze how human team organization affects overall mission success. Kane’s research provides essential insights for designing effective human-robot collaboration systems, making her work highly relevant for students and researchers in robotics, human factors, and autonomous systems.