A lidar technology company and a robotics AI developer have announced a collaboration to improve how general-purpose robots perceive and navigate complex environments.

The partnership between San Francisco-based Ouster and California -based FieldAI combines high-resolution lidar technology with a universal robot intelligence platform designed to operate across different robot types, tasks, and environments.

The system enables robots to be deployed at new sites without prior maps, pre-planned routes, supporting infrastructure, or environmental modifications.

“Scaling autonomous systems in demanding real-world conditions starts with advanced sensor technology,” said Andrew Mullen, Head of Hardware at FieldAI, in a statement.

Robots gain perception

The collaboration between Ouster and FieldAI aims to accelerate the deployment of autonomous robots in some of the world’s most challenging industrial environments by combining advanced sensing hardware with general-purpose robot intelligence.

The partnership centers on the integration of Ouster’s Rev8 native color digital lidar technology with FieldAI’s Field Foundation Models, a robotics AI platform designed to enable autonomous operation across a wide range of robot types, tasks, and environments. The companies believe the combination can help robots perform reliably in complex, unstructured settings where traditional automation systems often struggle.

FieldAI has developed what it describes as a universal robot “brain” capable of operating across radically different robotic platforms. Unlike conventional robotic systems that typically require detailed maps, carefully planned routes, specialized infrastructure, or extensive site preparation, FieldAI’s technology is designed to allow robots to enter a new worksite much like a newly hired employee. The robots can assess unfamiliar surroundings, understand environmental conditions, and begin operating without prior knowledge of the location.

At the core of this capability are the company’s Field Foundation Models, large-scale AI models trained to understand and interact with the physical world. These models are intended to help robots navigate unpredictable environments where terrain, obstacles, equipment, and working conditions can change continuously. Such environments include construction sites, mines, industrial facilities, energy infrastructure, and remote operational areas where conventional robotic systems often face significant limitations.

To support these capabilities, FieldAI relies on Ouster’s digital lidar sensors, which provide a detailed three-dimensional perception of the surrounding environment. Lidar technology uses laser pulses to measure distances and generate highly accurate spatial maps. Ouster’s latest Rev8 platform adds native color perception to lidar data, enabling robots to capture richer environmental information while maintaining precise depth sensing.

Scaling physical AI

The Rev8 digital lidar platform is designed to deliver high-resolution perception in conditions where cameras or GPS-based systems may be less effective.

According to its developers, it is particularly important in unmapped environments, indoor facilities, underground operations, and GPS-denied locations where autonomous systems must rely heavily on onboard sensing. The technology’s rugged construction also makes it suitable for deployment in harsh industrial conditions involving dust, vibration, weather exposure, and heavy machinery.

FieldAI already uses Ouster’s lidar technology to support navigation and autonomy in complex operational settings. As the company expands deployments with major industrial customers, it plans to incorporate the enhanced sensing capabilities of the Rev8 platform to further improve robot safety, environmental awareness, and decision-making. The addition of native color data is expected to provide greater interpretability of robot actions and improve the ability of autonomous systems to identify and understand objects and conditions in their surroundings.

The collaboration is expected to support the broader adoption of physical AI systems across industries where labor-intensive, hazardous, or difficult-to-access tasks remain challenging for human workers. Target sectors include construction, mining, energy production, manufacturing, security operations, and government applications.

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