A multicamera tool that ensures safer
operations using machine learning

A multicamera tool that ensures safer operations using machine learning

Advanced Safety and Intelligent Mobility through Onboard Vision (ASIMOV)

The ASIMOV system provides day-or-night, 360-degree awareness of personnel. ASIMOV can continuously track stationary and moving pedestrians while anticipating the movements and intentions of friendly versus hostile combatants. Offering constant surveillance, ASIMOV enables maximum mobility while maintaining the vehicle’s safety radius. The system avoids active sensors such as lidar or radar, which can compromise covertness. Instead, it uses cameras and machine learning algorithms to distinguish between friendly and hostile pedestrians.

Military tank vehicle with cameras tracking friendly personnel, hostile actors, and bystanders

“We are developing fast, robust technologies for reliably detecting and tracking people in challenging environments and situations.”

Camille Monnier,
Principal Scientist and Principal Investigator on ASIMOV

Operational safety is paramount to successfully deploying driverless systems, as they will operate alongside soldiers, bystanders, and hostile actors. Therefore, these systems must be equipped with a sensing solution to avoid collisions and enemy threats, among other safety concerns.

By improving the safety of automated vehicles, Charles River Analytics expects that the full-scope ASIMOV system will contribute to deploying and adopting robotic combat vehicles throughout the armed forces. As trust in robotic vehicles among personnel grows thanks to tools like ASIMOV, overall confidence in the Army’s autonomous ground systems is expected to increase.

Contact us to learn more about ASIMOV and our other robotics and autonomy and computer vision capabilities.

This material is based upon work supported by the ASA(ALT) SBIR CCoE under Contract No. W51701-22-C-0062. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the ASA(ALT) SBIR CcoE.

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