aiqbench analysis
This research addresses the critical challenge of intent inference in human-robot teams, specifically within high-stakes search-and-rescue scenarios involving heterogeneous autonomous agents. By developing a platform to study operator behavior and support decision-making, the work advances the practical integration of AI into complex, dynamic environments where human perception must be augmented by machine intelligence.
Towards Intent-Aware Human-Robot Teaming: A Platform for Search-and-Rescue Operations
arXiv:2609.26051v1 Announce Type: new Abstract: We investigate the challenges of enabling effective collaboration between human operators and heterogeneous autonomous agents in complex, dynamic environments by developing an interaction platform that allows study of operator behavior and supports intent inference and decision-making using state-of-the-art frameworks. We demonstrate the extent to which the operator's perception, decisions, and actions could be supported by autonomous systems during search-and-rescue operations with our platform.
Abstract:We investigate the challenges of enabling effective collaboration between human operators and heterogeneous autonomous agents in complex, dynamic environments by developing an interaction platform that allows study of operator behavior and supports intent inference and decision-making using state-of-the-art frameworks. We demonstrate the extent to which the operator's perception, decisions, and actions could be supported by autonomous systems during search-and-rescue operations with our platform.
Robotics (cs.RO)
arXiv:2609.26051 [cs.RO]
(or arXiv:2609.26051v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2609.26051 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 156 words
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