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Autonomous Search and Rescue Online

We propose a technique for autonomous robotic navigation of unknown environments with applications to urban search and rescue. By utilizing a deep reinforcement learning approach we maximize the search coverage while avoiding unknown obstacles. Allowing autonomous platforms to rapidly search and provide feedback to rescue teams has the potential to aid both the victim and rescue personnel. Through a simulation study, we find that this approach searches significantly more area over time than a conventional map-based frontier exploration. 

Date:
Friday, April 23, 2021
Time:
12:00pm - 1:00pm
Time Zone:
Pacific Time - US & Canada (change)
Online:
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Event Organizer

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Matthew Cook

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