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Lidar-maker Ouster buys vision company StereoLabs as sensor consolidation continues

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Lidar-maker Ouster has acquired StereoLabs, a company that makes vision-based perception systems for robotics and industrial applications, for a combination of $35 million and 1.8 million shares.

The deal is the latest in a march toward consolidation among perception sensor suppliers. Just last month, MicroVision bought the lidar assets of the buzzy-but-now-bankrupt Luminar for $33 million. Ouster itself has played the M&A game a fair amount, too. In 2022, the company merged with rival player Velodyne. The year before that, it bought lidar startup Sense Photonics.

This consolidation is happening right as companies and investors rush to build businesses around “physical AI” — a broad term that encompasses everything from humanoid robotics and drones to self-driving cars and automated systems in warehouses. Even more obscure suppliers are raising big funding rounds as these technologies develop. Some startups are even trying to spin up entirely new sensor modalities.

Ouster co-founder and CEO Angus Pacala told TechCrunch in an interview that he had been eyeing StereoLabs for years. He said he sees lidar as “the core component of safety-critical, capable systems,” but that he wanted to “move up the stack.”

The “obvious additional sensors” to start working with in addition to lidar, Pacala said, are cameras. Pacala said 15-year-old StereoLabs is “best in class” on the hardware side, but he was especially drawn to how the company has been getting the most out of those cameras by being “incredibly savvy in adopting the cutting edge of AI models and edge compute.”

In particular, Pacala highlighted StereoLabs’ development of a foundational AI model that can determine depth of objects from stereo cameras.

“It was a no-brainer for us to go out and approach them and basically pitch this vision of working with us to become a unified sensing and perception platform — a tier one [supplier] for these advanced physical AI systems,” Pacala said.

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