Project RICSAARS - Remote information collection, situational awareness, and adaptive response system

VESS (a small business developing and commercializing next generation aerospace, geospatial, and biomedical solutions), in collaboration with Rochester Institute of Technology (RIT) and extended team, is developing a threat detection and identification solution for unmanned vehicles capable of enhancing an unmanned vehicles ability to detect (through on-board visual cameras, LIDAR, and sensors), avoid, and dispose of environmental threats. The team will build off the 1st generation variant of the system (developed by the U.S. Navy) to develop a 2nd generation variant capable of facilitating improved automated and manual response to environmental threats. Addressing the DOD's need for effective "autonomous, intelligent maneuver and behaviors of autonomous ground and air vehicles through AI/ML enhanced object recognition, and threat warning" (Army Futures Command - Project Convergence). The proposed system is an adaptive situational awareness, decision support, and automated response system, operable to recieve sensor data or battlespace data for a region of interest along or in advance of a path of travel. Specific environmental conditions that can be identified via the 1st generation vision-based functionality, which interfere with the vehicle include damage to a road, traffic conditions, and weather hazards. The system technology can then utilize a mobile inspector functionality based off of both visual and frequency signal readings, which overlay video images and RF frequencies to detect conditions or anomalies such as IEDs and placed threats along a path of travel by a mobile platform. As a system moves through an unsafe area and detects threats, the technology can warn and utilize an internal route planner to reroute the unmanned unit and avoid a detected threat. The 1st generation technology has been proven for unmanned mobile reconnaissance vehicles (UMRV)/unmanned aerial vehicles (UAV) searching for, and analyzing, the frequencies of devices in the path of a mobile control vehicle (MCV) to locate conditions of interest and relay this information to the MCV. The team will work with the Air Force to develop a 2nd generation variant of the system capable of being employed by an unmanned vehicle to provide vision and RD-based frequency overwatch detecting anomalies and threats for force protection (mobile unit and base security), unmanned vehicle navigation, and ordinance detection/disposal.