Collaborative Autonomy for Robots Using Signals of Opportunity (CARUSO)
Department of Defense
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Charles River Analytics Inc.
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Vice President Finance
Vice President Finance
AbstractUrban combat presents the warfighter with significant and complex challenges, especially when dealing with targets that are located deep within buildings and other structures. Unmanned ground vehicles (UGV) have proven useful in providing remote reconnaissance for indoor environments and there has been recent interest in using these platforms to emplace micro-munitions for precision attacks on strategic targets. Indoor navigation and search is a challenging problem for tele-operated robots due to lack of situational awareness, especially since GPS signals are generally not available. Signals of opportunity such as TV, radio, cellular and 802.11 (WiFi) can penetrate structures and can potentially be leveraged for navigation. On this basis, we propose a system called Collaborative Autonomy for Robots Using Signals of Opportunity (CARUSO). This approach is based on the classic Simultaneous Localization And Mapping (SLAM) approach to navigation but uses several enhancements to improve performance. We also use signals of opportunity like WiFi to perform indoor geolocation comparable to GPS. Finally, CARUSO is designed to operate collaboratively between multiple platforms enabling data sharing and cooperative localization which enhances the overall navigational capabilities of the system. Our approach leverages the same methods that allow devices like the iPhone to self-localize without using GPS. BENEFIT: The proposed technology will have immediate applications for DoD customers who use mobile robots in both reconnaissance and munitions placement programs. In the private sector, cooperative navigation for mobile agents will be useful for fire departments (for search and rescue), bomb squads, and SWAT teams. SLAM capabilities will be applicable in almost every scenario where mobile robots can be of service including hospitals and warehouses.
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