Podcast: talking lidar and connected car platform
(Image credit: Blaize)

Podcast: talking lidar and connected car platform

In the latest embedded edge with Nitin podcast, you'll hear about lidar and connected car platforms, specifically featuring interviews with Ted Tewksbury, CEO of Velodyne Lidar, and Sarah Tatsis senior vice president for the Ivy platform development at BlackBerry.

On the state of lidar

Ted explains why it’s a very exciting time for the lidar industry. He told me, "It brings benefits in terms of safety, sustainability and efficiency to a wide range of applications, everything from autonomous vehicles to industrial and robotics, to smart cities and many other applications. So I’m very bullish on lidar in general. Right now we’re at an inflexion point where we’re starting to see the first R&D projects that come out into pre-production and then very shortly into full production."

"We have as of now over 200 projects in our pipeline, and 35 of those are multi-year agreements and so having some of those start to move into production is very exciting."

On the company's key strengths, he said, "We see a lot of competitors who are developing singular products for very specific applications in use cases and the most popular one that you see out there is automotive and ADAS and we are also very interested in ADAS. But what we see is that the L2 plus and the L3 and higher levels of ADAS continue to push out for a variety of reasons, so we’re really focused on near term opportunities."

"What we see to be an enormous market that’s largely being ignored by other competitors out there is in industrial and robotics. We’re seeing a drive to implement more robots on the factory floor and on the warehouse, in order to move goods very efficiently around to enable better social distancing and help alleviate the worker shortage and the supply chain issue.

We’re seeing a lot of interest in lidar based automation on ship cranes and helping ships get to get to navigate safely to the dock, and then we’re seeing last mile delivery vehicles that get from the warehouse to the consumers front door.

On connected car platforms

Meanwhile, in the second part of the podcast, Sarah Tatsis explained that BlackBerry Ivy is an edge-first implementation of a vehicle-agnostic platform that does the hardware abstraction and then enables the running of machine learning and other algorithms in the vehicle. 

She said, "Now in terms of what differentiates that from other implementations, most automakers are doing something similar although for very specific experiences that they’re already putting into their connected vehicles. What we’re providing is a scalable platform that can be implemented across various vehicle makes and models which also very much reduces the developer friction for creating new experiences in vehicle. So in other words over time, you could add new insights being generated within BlackBerry Ivy that power new applications over the lifetime of the vehicle."

She said at at CES the company was showing BlackBerry Ivy working on an NXP i.MX 8 hardware board. "Ivy itself actually is platform and operating system agnostic, so you can actually put this on any automotive grade hardware and also, on top of any operating system that’s working in the vehicle. We are also showcasing this working on a Linux operating system. And then from a digital cockpit perspective, we’re actually integrated into KPIT’s digital cockpit."

So within the vehicle, essentially it’s using the KPIT Technologies cockpit to consume the insights that are coming from Ivy. Within Ivy itself we’ve implemented multiple synthetic sensors is what we’re calling them, but it’s essentially machine learning models and algorithms that take real vehicle data and then provide these really interesting insights. So what we’re showcasing at CES is one specific version of what you could do with Ivy related to EV vehicles and it’s focused on a use case around a family that’s essentially taking a trip to the beach and wants to basically reduce their range anxiety of their EV vehicle and also make use of all these other great experiences."

To hear the full interview with Ted Tewksbury of Velodyne Lidar and Sarah Tatsis of BlackBerry, listen to the podcast here.

Is the general expectation that LiDAR data will be processed on the device/robot, or streamed to a remote edge server or cloud? I’m trying to understand the connectivity impacts of industrial LiDAR - how much data (say from a LiDAR sensor on a crane or AGV) would be sent over the network vs consumed or filtered locally?

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