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Human-Machine Teaming on the Battlefield: Improving Warfighter Safety with Drone Swarms

Charles River Analytics Inc., developer of intelligent systems solutions, has been awarded a contract option as part of DARPA’s Offensive Swarm-Enabled Tactics (OFFSET) program. Under our Swarm Algorithms and Tactics for Urban Reconnaissance and Isolation (SATURN) option effort, we will now integrate SATURN capabilities into the overall OFFSET program. These capabilities provide heterogeneous swarms of unlimited size with resilient swarm behavior to achieve military objectives.

DARPA OFFSET

DARPA’s OFFSET program aims to make small-unit combat forces operating in urban environments more effective with highly autonomous swarm technologies

Unmanned air and ground vehicles provide countless benefits in urban missions—drone swarms can help keep our Warfighters safer by performing risky missions, such as intelligence gathering, surveillance, and reconnaissance. OFFSET is actively developing 100+ operationally relevant swarm tactics that could be used by groups of unmanned air and/or ground systems.  A principal goal of OFFSET is to make it easier for Warfighters to develop and share swarm tactics in rapidly evolving urban settings, and free up Warfighters to perform other critical tasks.

Charles River is one of the “sprinter” teams that was selected to develop tactics for successful swarm deployment. We have created and tested our own novel swarm tactics within the OFFSET testbed environment, working closely with DARPA and the integrator teams to implement our collective ideas.

“During the base period, we successfully developed tactics, primitives, and algorithms for urban swarm operations. Now, we get to integrate them into the OFFSET Swarm System Integrators’ simulation environments,” said Dr. Spencer Lynn, Senior Scientist at Charles River Analytics.

Our OFFSET participation complements other techniques and applications Charles River has developed to support autonomous and unmanned systems, such as the MINOTAUR interface for controlling robotic leader-follower systems, the AMPT framework for supervising unmanned vehicles, and the CROWSNEST maritime traffic awareness solution for an unmanned surface vessel.


This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR0011-18-C-0077. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the Defense Advanced Research Projects Agency (DARPA).

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