Open Problems in Robotics

Robotics is simply hard, from algorithmic, computational, and engineering perspectives. Only some parts of it can be solved by throwing money and raw compute power at it. Even in areas where progress has been made, you generally need experts to decompose the problem at hand into something that can be tackled with existing techniques,and those experts are expensive and in relative demand.

Climate change isn't a "tail risk". It is a hard wall our civilization is approaching fast. If we do not solve it, it will undo the conditions we depend on to live.

As far as large lenses and sensors not working well on sensors, I think you'd be surprised just how well large lenses designed for the sensors they belong on can work. Indeed, by far the reason why photography lenses are huge is because of lens IS and zoom. Making small, light, fast normal lenses with larger stabilized sensors works perfectly fine and can be made very light.

After all, humans have two huge sensors (slightly bigger than full-frame) with f/3 lenses, and it works perfectly fine.

Now, to what I think is missing from the state of the art in robotics:

>Phase-detection autofocus is so fast in part because it's only using a sparse set of autofocus points, rather than the full sensor resolution.

This was true a decade ago, but now if you look at Canon sensors or some Sony sensors not subject to the patent, every single pixel is a phase detection point. Indeed, the pixels are cut in 2 or 4 photodiodes each only receiving light from one half or one quarter of the aperture.

This means that every single pixel can detect phase information, all 45 million of them.

Herein lies the major difference between Structure from Focus and phase detection : in a phase detection system, it is not needed at all to run a focus cycle. Instead, two waveforms are generated, one corresponding to one section of the aperture and one corresponding to another section of the aperture.

The two waveforms "match" when the incident rays correspond to the same point, that is to say, when focus is achieved. However, it really isn't necessary to actually achieve focus - focus simply offsets the phase of the two waveforms.

Therefore, by simply computing the phase difference of the two waveforms, one can instantly know, given knowledge of the lens characteristics, the distance of the subject, without having to achieve a focus cycle (!)

Indeed, phase detection actually works very similarly to parallax, in that in actuality you can use it to construct two split, offset images.

Of course, you can also use two stereo cameras, but then you have the issue of having to motorize the cameras to achieve convergence, without which stereo overlap is minimimal, wherehas per-pixel phase detection provides complete overlap and is much more precise.

If you want to see this in practice, the RAW files of a Canon EOS R5 actually encode distance information for every single pixel.

Also,

>the depth value is only as accurate as the depth of field

Yes. The depth value is precise, in a modern camera, to about one 5000th of the diameter of the aperture, which is, for a 50mm f1.8 normal lens, able to compute depth accurately for any subject within 50-60 meters. Which is better than LiDAR of the the same size, easily. And you can do so for a small fraction of the cost by simply upgrading hardware that is already necessary.

It is true that modern cameras actually do move the focus and re-calculate depth, which might give the impression that if you wanted to calculate depth you would actually need to move focus. But in reality, this is done in order to correct for the small misalignment in different lenses, as well as for the fact autofocus motors do not have accurate encoders and will very frequently miss steps. But a modern camera already knows how much the image plane needs to actually shift before even engaging the autofocus motor at all.

In essence, SfF in the State of the Art is an inversion of the state of autofocus 20 years ago, using contrast detection as the autofocus method. However, modern autofocus has progressed so much in this time-frame that it has solved almost all of the issues of SfF.

But this is largely because modern lenses are seriously bloated, with IS for older cameras that have non-stabilized sensors, bloated focusing mechanisms to make floating elements work, bloated zooming mechanisms that make everything so much worse, and so on.

If we want to design a lens for robotics, we really don't need much more than a double-gauss normal lens with a unitary focusing mechanism.

One of the lenses I use when I need to kludge something in a project is exactly that, a 1970s Minolta 55 f/1.7 lens for a full-frame image circle. Despite having a large 32mm aperture, it has a diameter of 56mm and a length of 44mm. I don't know if that's too large for your robotics applications, but it isn't very big and it's much smaller than the LiDAR sensors I've worked with. You could likely make this even smaller with modern techniques. It would also cost about 40$ to build.

>The human eye is vastly more complex and capable than a fixed plane imager and capable of much more complex focus behavior than any existing lenses are. Camera-eye comparisons are appealing, but the focus behavior of them is really very different.

My point was moreso that in pure optical sizes, the human eye is bigger and takes up more volume than the optical system I'm proposing. But as far as focusing behaviours, if you were to mathematically model how the human eye gets depth information to drive the focus cycle its quite similar to a phase detection system, with the phase information being extracted through the parallax.

>Canon has done a very nice job with their autofocus, but I will believe they have solved depth perception with phase detection when they apply it to their industrial cameras. Canon makes very nice RV-series parts recognition cameras that do a very good job with challenging materials, but they use structured light. In theory, phase-detection SfF would be perfect for these cameras but they haven't done it.

I think this can be explained quite simply. In a fully controlled environment, using structured light but cheap lenses and small sensors is much more cost-effective. Why would they use expensive APS-C+ sized sensors, that they don't seem to be all that good at making, when you can get away with very cheap parts?

>The minor problem is that you generally want depth plus RGB, which is obviously solved by adding a second camera but then you face basically the same size and overlap issues that stereo cameras bring. Not entirely a free lunch.

But this is precisely the point of OSPDAF or split-pixel phase detection. You get both depth and RGB at the same time, because the RGB sensor doubles as a phase detection sensor. It's not like old cameras where you had to use a mirror that sent light to the dedicated phase detection sensor.

As for political problems, I agree. Canon won't ever sell you their DPAF sensors. Sony, even though they are really bad at robotics, should in theory be willing to sell anyone their sensors, and it should be possible to make a prototype. Their tech in this would be limited relatively to Canon, though.

But, to the point, a solution to a problem that's proprietary is still a solution to the problem.