Microvision Fast-tracks Adoption of Luminar Tech

May 5, 2026

Chris Clonts

In the two months since Microvision bought Luminar and acquired key tech and talent, the sensor company has been busy.

In that time, they’ve merged key lidar units from each company and created a perception software stack to run it in a convincing demo of its ADAS and autonomous capabilities.

The company is also pushing innovative lidar tech into the defense drone and antidrone markets, already working with a German defense supplier that works with NATO member countries.

The company revealed all this to SAE Media as part of an exclusive presentation to select journalists on the eve of the Advanced Clean Transportation (ACT) Expo in Las Vegas.

In February, Microvision CEO Glen Devos had his work cut out for him, saying the biggest priority was restoring relations with customers that had soured as Luminar fell off the cliff into bankruptcy.

Greg Scharenbroch, Microvision’s vice president for global engineering, said that effort had gone well and that the company was working with 50 new client companies across all sectors. He said that application diversity is what can carry the company forward into a stage that the company calls lidar 2.0.

He said lidar 1.0, the original development phase, resulted in capable technology that had too high a price point. “The mindset of Silicon Valley was to focus on performance, deliver the highest performance system and solution that you can get, and then over time, volumes will come and prices go down,” he said. “But that’s not really what happened.”

Scharenbroch said many companies that operated then do not now (including Luminar). “I mean, we see Waymo cars still around, but that’s a very unique situation with a parent company with very deep pockets,” he said.

Among the company’s pillars for success is developing a core technology that can be applied in many sectors. Tech “that’s modular and scalable and reusable with very little incremental effort across automotive, commercial vehicle, industrial, and security and defense,” he said. “No. 2, we’re going to design to cost.”

In engineering terms, he said the goal was to design components to solve problems and to avoid what he called scope creep while delivering a solid return on development investment. He added that as hardware costs decline, software would be the differentiator among competitors.

As for products, he described four categories of capability:

Near/mid-range lidar (up to about 55 m/180 ft): MOVIA L, a modular unit that can accept different optics easily, and MOVIA S, a more compact and cost-effective unit easily embedded in body panels.
Long range (255 m/836 ft and beyond): HALO, which is one-third the size of the more-tenured IRIS sensor but with up to four times the performance due to its wavelength of 1500 nm, which can see farther without endangering eyes. These were the Luminar acquisitions.
Ultra-long range (325 m/1,066 ft and beyond): HALO and frequency modulated continuous-wave (FMCW) lidar.
The software stack that allows perception: The computational 3D representation of the environment.

To facilitate the rollout of the FMCW product, Microvision acquired Scantinel and its 50-mm single-chip that provides wafer-level integration of the package. Scharenbroch said that eventually, the system would be able to scale out to about a kilometer (0.62 miles). That’s far more than most ground transportation modes would ever need. What use could it have? Defense.

On the road, live

Microvision’s new combination-lidar demonstration vehicle, a Volkswagen Tiguan. The HALO sensor can be seen on the roof, while MOVIA S is mounted just ahead of the A-pillar. (Chris Clonts)

In a revealing demonstration of where they’re headed, Microvision had a few journalists at a time pile into a Volkswagen Tiguan outfitted with a HALO unit and MOVIA S units just ahead of each A-pillar and centered on the back bumper, facing rearward. The sensors were operating at 10 Hz, or 10 sample cycles per second.

As we drove around one of Las Vegas’ westside neighborhoods, the degree of differentiation being recorded by the Sentinel software stack was clear. Las Vegas has a lot of streets without sidewalks, where flat, slightly rough pavement gives way at the shoulder to very small bumps and valleys as little as 2- to 3-mm thick. Sentinel was showing that line clearly, highlighting the edge of the roadway with a thick red line.

Different sized vehicles were categorized consistently, cars and other passenger-size vehicles appearing in one color and trucks, SUVs and large trucks appearing in others. The system predicted in real time where their driving track was taking them, arrows smoothly curving around corners or into driveways as vehicles changed direction. At one point the system was simultaneously tracking and categorizing dozens of moving objects, from Class 8 trucks to passenger vehicles to a person on a bicycle.

The visual representation of the point-cloud data acquired by Microvision’s HALO and MOVIA S lidar units as consolidated by the Sentinel software stack. Despite little visual demarcation, the software shows the edges of the neighborhood street with bright red lines. (Chris Clonts)

The ultimate value of the system, according to software manager Paul Varcholik, was what Microvision calls localization. That is, once a street has been driven once, Sentinel stores a “digital fingerprint” made up of key points in the cloud (they show as white dots in the demo). Since one option is to store that first-pass information in the cloud, it means any other vehicle with Sentinel deployed would have that information even before it is in lidar range, effectively letting an ADAS/autonomous system or a driver see that much farther down the road.

A previous problem was the amount of data created, but Microvision has developed a compression scheme that ultimately needs only 600 kb per km of data.

Though it has been delayed, NHTSA intends more stringent tests for automatic emergency braking, especially around partially obscured children and pedestrians (for instance, a child standing between two parked cars who begins to bolt forward into the street). Scharenbroch said it’s an almost perfect use case for the HALO plus MOVIA system.

A close view of one of the MOVIA S units deployed on the demonstration Volkswagen Tiguan (Chris Clonts)

Real value for freight haulers

Scharenbroch laid out a convincing use case for adding lidar to Class 8 and other HD commercial trucks: The savings due to reductions in crash-related property damage, injury and fatalities.

He cited lidar’s value in reducing the cost per mile, starting with estimates of cost avoidance savings of 4 cents per mile attributable to crash mitigation. Insurance companies have reported 15% savings in accidents for fleets that deploy current ADAS features like auto braking and lane keeping. Those savings resulted in up to 20% lower premiums. He also cited data showing proper vision technology can reduce rapid decelerations, which smooths speed profiles, increasing mileage and reducing wear and tear, a savings of up to 8 cents per mile.

“There are about 3 million to three and a half million Class 8 trucks in the U.S., and every year there are about 650,000 crashes,” he said. “Of those, about 400,000 result in property damage and 150,000 cause injuries.” He said those numbers would drop quickly once SAE Level 4/5 autonomy is reached, because trucks could operate at night when there is less chaotic traffic.

A study by NHTSA indicated that human error causes 94% of all vehicle crashes in the United States.

Defense, other applications

Scharenbroch shared a few intriguing uses in defense applications. One would be using lidar from fixed positions to monitor perimeters for motion and intrusion. Imagine a lidar detects an incoming drone, and could relatively easily identify the kind of drone and, in turn, decide the best method of neutralizing it, whether by jamming, direct fire or some other method.

He said some such early systems had trouble distinguishing between birds and drones. But Microvision’s lidar can produce fine resolution enough to see tiny mm differences in a road surface – ID’ing a drone would not be a monumental challenge. “We’ve done proof of concept for multiple customers and created prototypes for evaluation,” he said.

In addition, a lidar-equipped drone deployed ahead of a ground fighting vehicle like an M2 Bradley could effectively see into obscured areas, through foliage, camouflage netting and more, getting info to tactical leaders, reducing uncertainty and giving them a longer decision timeline.

The company also wants to use its products to increase safety around the use of automated forklifts and automated guided vehicles (AGVs). AGVs follow prescribed paths and stop when there is traffic or an obstruction. This can slow parts making it to the right place on time on a factory floor. Lidar-guided autonomous mobile robots (AMRs) can create their own efficient path around obstacles and people, which also would reduce industrial accidents.

How to stay in business

Back to the company’s core business tenets. Scharenbroch said that one final pillar of the company’s plans was financial discipline, and it was clear it has learned lessons from the failure of Luminar and other companies.

“We have a fixed budget, we have a spending envelope, and we have a run rate, and we don’t go beyond that,” he said. “What we saw here was massive outlays of capital before volumes materialize, and we’re not going to do that.”