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NRI: INT: Balancing Collaboration and Autonomy for Multi-Robot Multi-Human Search and Rescue

Each year, thousands of people go missing in the United States. Coordinated search and rescue (SAR) operations provide the best chance to locate a missing individual alive. However, challenging terrain and other search constraints represent a barrier to human searchers. This project therefore seeks to enable collaboration between human searchers and unmanned aerial vehicles (UAVs) to improve searches while reducing human effort. Specifically, this project asks: How do we select and assign search tasks that ensure long-term human-robot collaboration, while deploying robots to complement human searchers in real-time? This project aims to answer this question through optimization, behavioral modeling, human-robot interaction, and computation, with evaluation in large-scale prototypes supported by the SAR community. Finally, impacts beyond SAR include: (1) education focused on co-robots; (2) theory for human-robot interaction in collaborative settings; (3) portable, low-cost, low-power computational infrastructure suitable for a wide range of applications; (4) technologies that foster economic opportunity around co-robots; and (5) field experiences for students from groups underrepresented in engineering.

This project focuses on new theory and technologies for: (1) a minimally invasive, adaptive, multi-UAV control system leveraging risk-aware multi-robot planning for human-in-the-loop (HITL) control; (2) distributed computing that opportunistically exploits and balances multi-robot interaction, communication, computation, and decision-making; and (3) an interface between human searchers and UAVs that allows control from complete autonomy to manual operation, including testable interfaces for exploration vs. exploitation strategies. This project addresses fundamental challenges critical to the scalability of multi-robot multi-human teams: (1) planning and control systems for UAVs that can autonomously gather information in a cooperative and distributed way while adapting to uncertain human plans; (2) interfaces for human-robot interactions that allows collaboration that appropriately balances exploration with exploitation; and (3) real-time support to analyze, store, and share data subject to the power and connectivity constraints typical of real-world deployments.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Principal Investigator

Ryan Williams

Project start date

10/1/2018

NSF

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Researchers aim to enhance lost person search and rescue efforts using drones, artificial intelligence