In modern warfare, seconds can decide the outcome of a mission. Responding quickly to fast-changing threats on the battlefield is no longer optional; it’s essential.
To meet this demand, Lockheed Martin has partnered with IBM’s Red Hat to develop a new generation of autonomous drone swarms that can think faster, move smarter, and adapt in real time.
Smart drone swarms
At the core of this capability is integrating Red Hat’s lightweight, container-based software system, Red Hat Device Edge (RHDE), into Lockheed Martin’s existing swarm autonomy framework.
This allows for rapid, secure software updates directly to drones operating at the edge of contested environments without returning to base.
The result is a living, evolving swarm that can upgrade itself mid-mission to counter new threats.
The drones being used in this program include the Indago 4 Uncrewed Aerial System (UAS), a tactical quadcopter developed by Lockheed Martin’s Skunk Works.
Equipped with 360-degree surveillance capabilities, the Indago 4 is now enhanced with onboard AI and machine learning.
These technologies allow swarms to execute multi-step missions, reassign tasks mid-flight, and dynamically respond to unknown situations.
Swarm tactics under this system focus on maximizing efficiency and adaptability through coordinated operations.
One key aspect is the coordinated area search, where drones fly across a wide terrain.
By sharing live intelligence among themselves, they significantly reduce search time, allowing for quicker response and resource allocation.
Another important tactic is dynamic re-tasking. The swarm is designed to adjust accordingly if a drone is lost or encounters a new threat.
This involves redistributing tasks among the remaining units, ensuring mission continuity, and maintaining operational effectiveness despite challenges.
Threat avoidance is a crucial feature of these swarm tactics as well. By utilizing shared data, the drones can collectively identify hostile systems and reroute them in real-time, enhancing their survivability and mission success.
Lastly, collaborative targeting plays a significant role in the swarm’s effectiveness. Multiple drones can track a moving target simultaneously, relaying data to one another to enable precision strikes or interdiction.
This level of cooperation maximizes the impact of their operations and improves overall mission outcomes.
Think and hunt together
Katie Gilmore, Program Manager at Lockheed Martin, said, “This work helps UAVs receive updated software modules on the fly, transforming how we manage and update edge devices. This is critical for future missions, giving drone swarms far greater abilities to protect people and infrastructure in real-time.”
Lockheed Martin’s use of open architecture makes the system even more adaptable. New capabilities from commercial, defense, and non-traditional partners can be added quickly without major redesigns.
As new AI models, threat databases, or flight controls are developed, they can be integrated and pushed to the swarm across secure networks, extending the swarm’s capabilities with minimal downtime.
This approach also strengthens deterrence. Smarter drone swarms can fly longer, travel farther, and operate deeper in denied airspace.
Their ability to adapt mid-operation makes them more resilient in complex and chaotic combat environments.
By operating autonomously at the tactical edge, they reduce reliance on centralized command structures, which are often targeted in high-end conflict.
Lockheed Martin’s collaboration with Red Hat shows how US defense contractors are merging commercial tech with mission-critical systems to stay ahead of emerging threats.
With AI-enhanced swarming, modular software updates, and edge autonomy, this program delivers a force multiplier for future air operations.
This autonomous system thinks faster than the enemy and adapts faster than it can be countered.
Such technology is critical to ensuring operational dominance across future conflicts in a battlespace defined by speed, complexity, and electronic warfare.
