David Hall Unveils Cam-Lidar Drone Defense System
David S. Hall, the inventor behind lidar for autonomous vehicles and founder of Velodyne Lidar, has introduced Cam-Lidar, a new high-speed aerial detection system, announced in a press release. The technology is the first product from Hall Lidar Inc., a Montana-based company Hall established earlier this year.
Cam-Lidar integrates lidar, camera optics, and artificial intelligence to detect and track aerial objects such as drones at distances up to two kilometers. The system synchronizes lidar and camera feeds at 60 frames per second, providing real-time spatial visualization and predictive tracking. It can identify objects as small as a laptop moving at speeds near Mach 1.
The technology is designed to work alongside Hall’s proprietary magnetic electrical launch (MEL) system, which can deploy net-based drone capture tools multiple times per second. Together, the systems aim to deliver rapid, precise, and cost-effective drone neutralization for security applications including airports, energy facilities, and military bases.
Hall Lidar has developed a working Cam-Lidar prototype and is now accepting early orders and demonstration appointments from commercial and government partners.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Defense AI Brief or Daily AI Brief.
Also, consider following us on social media:
More from Defense
Oct 16 Saab Completes Sea Trials of Large Uncrewed Underwater Vehicle Oct 15 Bridge Defense Wins Software Agreement With Up to $63 Million in Initial Capacity Oct 15 Ukrainian Drones Hit Sberbank Data Center Planned for Supercomputer Oct 15 US Air Force Extends Use of PTC Servigistics Oct 15 Ukrainian Strikes Disrupt Yandex Services Across Central AsiaDefense AI Brief
Your weekly intelligence briefing on the technology shaping modern warfare and national security.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Leopard Imaging and Lumotive Introduce Sirius Max 3D Perception Platform
DoD Solution Raises $2.1 Million for Autonomous Drone AI
Benewake Launches NOVA20 LiDAR for Close Range Robot Safety
PDW Adds Booz Allen Autonomy Software to AM Drones
Delta and NVIDIA Collaborate on Level 4 Autonomous Driving
Daily AI Brief: the AI news that matters, in your inbox.