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Teledyne FLIR launches Prism Supervisor

Teledyne FLIR OEM, part of Teledyne Technologies Inc., today announced the release of Prism Supervisor - the latest addition to its Prism embedded software ecosystem - which integrates drone autopilot flight control systems with real-time AI-based observations, enhancing the capabilities of unmanned aircraft systems (UAS).

Image courtesy Teledyne FLIR

Prism Supervisor software empowers mission planners with a flexible programming framework and software development kit (SDK) to facilitate custom, intricate mission scenarios. During flight, Prism Supervisor adapts its autopilot functionality in real-time, dynamically generating mission segments and flight plans on the fly, minimising operator impact while improving mission success. For example, a Prism Supervisor-controlled UAV flying a search mission pattern can autonomously circle and alert the operator upon the detection of a human or threat.

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Dan Walker, Vice President of Product Management, Teledyne FLIR. "From behaviour and mission planning to dynamically adjusting in-flight operations, Prism Supervisor represents a significant advancement for drone autonomy through AI.

"It improves operational performance via single-click missions, opening up new possibilities for UAS operation from commercial to military use cases."

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Prism Supervisor simplifies the operator experience with a user-friendly graphic user interface (GUI) for mission planning, real-time mission visualisation, and execution. Available for desktop or mobile deployment supporting Windows, Linux, macOS, iOS and Android, the supervised mission management application streams and records detailed, full-frame-rate video, path visualisation and metadata. It can facilitate collaborative behaviours and synchronised mission execution among multiple unmanned aerial vehicles (UAVs).

Prism Supervisor expands Teledyne FLIR's Prism digital ecosystem of advanced AI and image processing. It provides a platform for deploying object detection, tracking and computational imaging on low-power processors, enhancing UAS mission performance and reducing development costs.

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