Applied Intuition Launches Off-road Autonomy Stack, Powering a New Era of Autonomous Systems on All Terrains

Solution features customizable software modules using latest AI and machine learning technology to navigate unstructured terrain.

MOUNTAIN VIEW, Calif., June 17, 2024 /PRNewswire/ — Applied Intuition, a vehicle software supplier for automotive, trucking, construction, mining, agriculture and defense, today announced its new off-road autonomy stack solution that can navigate complex unstructured terrain safely.

Off-road autonomy is highly complex. The dynamic and inconsistent nature of off-road terrain can impact basic autonomous vehicle (AV) system functions like obstacle detection and avoidance, creating challenges for safe and efficient off-road navigation. Off-road environments also pose safety risks and put a high cognitive load on operators. Autonomy stacks can address reductions in manpower while contributing to operational efficiency and increased productivity across various industries. However, they require complex infrastructure and can be costly and challenging to develop and maintain in-house.

To help organizations navigate these challenges, Applied Intuition provides a robust off-road autonomy stack that can run on production hardware and navigate in real environments. The technology has been designed by a team of experts who understand both the latest machine learning (ML) techniques and the constraints of rugged environments. The stack consists of separately factored modules that can be individually integrated into a customer’s robotics system.

“As more industries look to adopt AV technology, we want our software to be at the forefront of off-road autonomy,” said Peter Ludwig, co-founder and CTO of Applied Intuition. “Our off-road stack combines the latest AI and ML advances with traditional safety and systems expertise to deliver state-of-the-art performance in the most challenging environments. We’re confident our offering will deliver strong value to our customers.”

Applied Intuition’s newest offering includes software capabilities such as:

Simultaneous localization and mapping: Enables a vehicle to understand rough, unstructured, and unmapped environments without requiring a consistent or accurate GPS signal.
Perception and object tracking: Provides a high-fidelity holistic view of surrounding environments in real time, including semantic understanding and 3D geometric modeling, for both static terrain and dynamic objects.
Sensor fusion and calibration: Collects data across multiple modalities using both traditional geometric and cutting-edge ML methods.
Planning and controls: Navigates the vehicle along a safe and efficient path that avoids rollover, entanglement, and collision using an approach that is proven across multiple vehicle types and models.

Applied Intuition’s off-road stack works with the company’s base software platform, while supporting third-party integrations, secure environment testing and data management. Organizations can also use the off-road autonomy stack in conjunction with Applied Intuition’s definitive ADAS/AD toolchain for simulation-driven development. To learn more about the off-road autonomy stack go to appliedintuition.com/off-road-autonomy-stack.

About Applied IntuitionApplied Intuition is a Tier 1 vehicle software supplier that accelerates the adoption of safe and intelligent machines worldwide. Founded in 2017, Applied Intuition delivers the definitive ADAS/AD toolchain, a world-class vehicle platform, and an off-road autonomy stack to help customers shorten time to market, build high-quality systems, and create next-generation consumer experiences. Eighteen of the top 20 global automakers trust Applied Intuition’s solutions to drive the production of modern vehicles. Applied Intuition serves the automotive, trucking, construction, mining, agriculture and defense industries and is headquartered in Mountain View, Calif., with offices in Ann Arbor and Detroit, Mich., Washington, D.C., Munich, Stockholm, Seoul and Tokyo. Learn more at appliedintuition.com.


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