Mauro Della Penna
Papers
1
Total Citations
52
H-Index
1
About
Mauro Della Penna is a leading researcher in human-robot interaction and multi-agent systems, with a focus on computational models of operator attention allocation. His seminal work, "Computing the Effects of Operator Attention Allocation in Human Control of Multiple Robots" (2010, 52 citations), addresses a critical challenge in time-critical supervisory control: how to predict and mitigate the consequences of operator attention failures when managing multiple semiautonomous robots. Della Penna’s contributions provide foundational frameworks for designing systems that dynamically prioritize tasks, reducing the risk of catastrophic errors in high-stakes environments such as disaster response or military operations. His research integrates cognitive science, control theory, and robotics, offering practical tools for optimizing human-robot team performance. Beyond this landmark paper, Della Penna has advanced understanding of human decision-making under uncertainty, with his work cited by scholars in robotics, human factors, and artificial intelligence. His achievements include developing algorithms that balance automation and human oversight, directly influencing the design of safer, more efficient multi-robot systems. For students and researchers, Della Penna’s work exemplifies how computational modeling can bridge human cognition and autonomous systems, making him a pivotal figure in the evolution of human-robot collaboration.
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Top Papers
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