Threat monitoring for unmanned vehicles

Animal responses underpin threat monitoring system for autonomous vehicles

Roke Manor Research has developed a biologically-inspired threat monitoring system for autonomous land vehicles that emulates a mammal’s conditioned fear-response mechanism.

The system, known as Startle, uses a combination of artificial neural network and diagnostic expert systems to continually monitor and assess potential threats.

Startle was developed to provide enhanced situational awareness and early threat warning to both the autonomous vehicle and to its remote operator(s). Making use of existing hardware, Startle intelligently processes information from multiple on-board sensors, cueing systems to assess and confirm potential threats to the vehicle.

It combines two artificial intelligence techniques - a lightweight classifier and a goal prover - to direct sensor assets and select processing algorithms to assess possible threats. This allows for more efficient and more focused use of available processing power.

Mike Hook, principal consultant at Roke, said: “Startle reduces operator workload and improves vehicle efficiency on the ground by helping remote operators to respond effectively in complex mission environments. Operators do not want to be distracted from their mission and the time it takes them to turn their attention to a possible threat could be too slow to save the vehicle.

“Startle delivers local autonomy to a vehicle by providing a mechanism for machine situation awareness to efficiently detect and assess potential threats. This allows vehicle sensing and processing resources to be devoted to the assigned task, but if a threat is detected it will cue the other systems to deal with it swiftly before continuing its mission. These vital seconds could be the difference between mission failure and success.”

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