ModalAI, a Blue UAS framework manufacturer of autonomous drone technology, says it has developed the world’s smallest and most advanced autopilot built in the USA. Weighing only 16 grams, ModalAI’s VOXL 2 is designed specifically for GPS-denied, autonomous drones with obstacle avoidance.
VOXL 2 enables autonomy and communications for both indoor and outdoor drones using vision-based SLAM (simultaneous localization and mapping) technology and AI computing.
It is powered by the Qualcomm Flight RB5 5G platform and integrates a PX4 real-time flight controller with an 8-core CPU, a GPU and NPU that provide a combined 15 Tera Operations Per Second (TOPs), seven image sensors, and TDK IMUs, and barometer.
ModalAI is positive that this smaller-than-business-card and lighter-than-AA-battery supercomputer autopilot will enable the next generation of smaller, smarter, and safer drones. As Chad Sweet, CEO and cofounder of ModalAI, puts it:
VOXL 2 creates a major leap in computing capability for the drone industry. From developing the first Blue UAS Framework autopilot, VOXL, to unlocking 5G skies with the Qualcomm Flight RB5 5G Platform, this launch is an important milestone for us.
Also read: This 550-gram R&D drone can navigate indoors autonomously
Sweet goes on to explain that VOXL 2 was created with accessibility in mind. Over a dozen partners are already integrating the autopilot in their newest drone and ground robot fleets. In the meantime, quick integration is also being enabled by open-source flight control tech company Auterion.
Lorenz Meier, CEO of Auterion, explains:
Auterion OS is at the forefront of driving the drone industry toward a unified standard that will allow for interoperability between enterprise drones and services. We are pleased to collaborate with ModalAI to make Auterion OS available on VOXL 2. Developers looking to build solutions for enterprise drone users with global and open standards using a common infrastructure can run Auterion OS on VOXL 2.
VOXL 2 is available to buy now for $1,200 at ModalAI’s website.
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