Industry Briefing
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L3Harris and ARX Robotics Test Counter-Drone Sensing on Uncrewed Ground Vehicle
L3Harris Technologies and ARX Robotics have successfully demonstrated a robotic ground vehicle equipped with a counter-drone sensing system during the US Army’s Project Convergence-Capstone 6 experimentation campaign. This innovative approach allows for the deployment of sensors on a remotely controlled robot, reducing the risk to soldiers by keeping them away from potential drone threats. The demonstration utilized L3Harris' CORVUS-RAVEN counter-drone capability mounted on ARX Robotics' GEREON uncrewed ground vehicle. This setup enhances situational awareness by passively detecting signals associated with drone threats and providing critical bearing information. The ability to reposition the robotic vehicle as tactical situations evolve offers commanders a flexible alternative to fixed sensor locations. As small drones pose increasing challenges for modern militaries, the collaboration between L3Harris and ARX Robotics highlights the importance of modularity and adaptability in military technology. No further timeline was disclosed at the time of publication.
Military
Drones Illuminate Atmospheric Boundary Layer for Military and Energy Traders
Drones are being utilized to gather data that sheds light on the poorly observed boundary layer of the atmosphere. This information is crucial for military strategists and energy traders who rely on accurate atmospheric data for decision-making. The ability to observe this boundary layer is significant as it can influence weather patterns and forecasts, which are essential for military operations and energy market strategies. By enhancing the understanding of this atmospheric layer, drones are providing valuable insights that can lead to more informed strategic planning. Looking ahead, the continued use of drones for atmospheric data collection may expand, potentially leading to improved weather forecasting and strategic military applications. No further timeline was disclosed at the time of publication.
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