Autonomous Search and Rescue (ASAR) with Multimodal Identification
Perceptronics’ system for Autonomous Search and Rescue with Multimodal Identification (ASAR) employs AI and Machine Learning to provide an autonomous capability for rapid localization and identification of rescuees. ASAR includes RF sensors to localize rescue signals, computer vision techniques to identify rescuees, and flying cars to perform and extraction. Efficiency comes from using multiple cooperative vehicles that continuously and cooperatively execute information maximization algorithms to understand the environment. The core coordination and autonomy algorithms are highly scalable, which when combined with intelligent sensing reduces the need for many operators and allows for large autonomous eVTOL/UAMs teams and rapid response. We are proud to partner with The Robotics institute at Carnegie Mellon University on the computer vision components.
Perceptronic’s ASAR Capabilities Will Impact End Users as Follows:
ASAR will reduce significantly the amount of costly equipment, such as helicopters, needed for CSAR operations.
Team of vehicles doing completely autonomous coordination, with only high-level oversight from human operators, will reduce the required level of trained personnel.
ASAR will rapidly cover significantly larger geographical areas by relying on a distributed team of search vehicles.
The team of vehicle will be able to perform CSAR operations significantly faster and save more lives.
The abilities to build a cooperative picture of the environment and maintain it despite attrition and weather conditions will make CSAR operations more robust.
Ad hoc network communications will allow for continued operation even in communication-denied environments.
ASAR is a game changer for rapid response, reduced personnel and reduced equipment cost; ASAR can cover wider areas and can save more lives.
Problem/
Opportunity
Take advantage of capabilities to cooperatively find and rescue victims. Take advantage of unique capabilities to cooperatively find and rescue victims.
Proposed
Solution
Use RF from cell phones to roughly locate victims, computer vision to identify them, flying cars to bring them out. Teams of vehicles working cooperatively to achieve this.
Impact
Ability to rapidly respond to large scale disasters and get victims to safety. Radically novel approach that keeps rescuers safe and increases ability to save victims.