Great question @ghawkins.
TL;DR: It’s the optics. Wide FOV (160-deg.) is great for SLAM. We have narrow FOV (70 deg). You could use an OAK-D as-is for SLAM, similar to how you could use an Intel D455 for SLAM, but likely the T265 will outperform both (disclaimer: I don’t really know, just a guess).
Myriad X actually has a ton of features that enable great SLAM that Myriad 2 doesn’t (super-low-latency hardware-accelerated depth, hardware-accelerated feature tracking and optical flow, etc).
So using wide FOV optics on OAK-D would make it an insanely good SLAM camera.
So… I may have over-stated it when I said it’s not suitable for doing SLAM. What I should have said is that it was not architected with SLAM in mind (narrow optics). So in contrast the Intel T265 was architected to be a simultaneous localization and mapping device.
And yes, you nailed it on the optics WRT being optimized for SLAM (or not). So the main difference is the Intel T265 has a fisheye lenses optimized for wide field of view (163 degrees IIRC), so as to optimize optical tracking (the more of the world around you that you see, the better the tracking results) whereas our grayscale cameras are optimized for comparatively narrow field of view (~70 degrees) for producing better spatial neural inference results - i.e. object or feature positions in 3D space.
I’m also FAR from knowledgable about SLAM… so someone who’s great at it might come in here and say: “What the heck are you talking about? OAK-D as-is is ideal for SLAM for reason X, Y, and Z”.
One thing I do know is that the capability to run AI onboard, even in SLAM use-cases, can be quite powerful for ignoring moving objects/etc. and so producing better localization results in the presence of people, forklifts, other robots, etc.
And in fact actually use the exact same image sensor (OV9282) as the T265… so it’s as simple as different optics which would make the device optimized for SLAM or not. Where wide FOV is desirable for SLAM applications, and narrow FOV is favorable for real-time 3D object/feature neural inference application.
On other thing to note is that since OAK-D is open source, it is possible to use other camera modules - say ones like used in the T265 - and then in that case OAK-D would be a top-notch SLAM+AI camera. For example here is an OV9281 module which would allow fisheye lenses, and there are some options for direct-integrated fisheye as well.
And some companies have reached out about making OAK-D variants (based off our open source hardware here) with wide-angle OV9282-based cameras that these companies already produce. And we’re super excited for them to do so as it’s part of our goal with open sourcing - to allow folks to leverage all this and go optimize for other use-cases we either didn’t focus on or couldn’t even think of.
Thoughts?
I hope that helps!
Thanks,
Brandon