In case you spot a Lucid Gravity SUV blinged-out with sensors — and a self-driving system developed by Nuro — driving round San Francisco, likelihood is that’s an Uber worker taking a journey.
Choose Uber workers can now request a journey in a Lucid robotaxi by means of the Uber app, the newest section of testing forward of a deliberate public launch later this 12 months. Nuro, which supplied the replace in a weblog posted Monday, advised TechCrunch the autos are working in autonomous mode and have a human security operator behind the wheel as backup.
Whereas that is removed from a public launch, it does sign the businesses’ progress since asserting a partnership and multimillion-dollar funding in July 2025. Uber invested $300 million in Lucid and individually agreed to purchase “at the very least” 20,000 of the EV maker’s new Gravity SUV over the subsequent six years.
These EVs are geared up with Nuro’s autonomous automobile system, which is powered by Nvidia’s Drive AGX Thor pc. The Lucid Gravity robotaxi, which was revealed in January, is outfitted with high-resolution cameras, solid-state lidar sensors, and radars that assist the self-driving system understand the real-world atmosphere and function in it.
Uber additionally invested an undisclosed “multi-hundred-million greenback” quantity into Nuro.
The plan is for Uber to personal and function — seemingly with the assistance from a 3rd get together — the premium robotaxi service. Manufacturing of those modified Lucid Gravity autos is anticipated to start in late 2026, in accordance with a regulatory submitting posted final 12 months.
Nuro accomplished closed-course testing and began its first public street testing of the autonomous Lucid Gravity SUVs late final 12 months. Nuro now has 100 Lucid Gravity SUVs outfitted with its self-driving system within the engineering fleet, used to assemble real-world information and take a look at autonomous driving throughout a number of U.S. cities and states.
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In response to Nuro, the worker take a look at rides assist the workforce consider how the autonomy stack, automobile, and rider expertise work collectively and performance in a dwell working atmosphere. It additionally permits the workforce take a look at how properly the automobile handles rider pickups and drop-offs, a notoriously difficult operation in autonomous ride-hailing.
