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Bill Gross, Heliogen’s current CEO previously founded eSolar. eSolar proposed using an array of Heliostaticly controlled mirrors to direct light toward a solar

by new299 7y ago

Bill Gross, Heliogen’s current CEO previously founded eSolar. eSolar proposed using an array of Heliostaticly controlled mirrors to direct light toward a solar cell: https://en.wikipedia.org/wiki/ESolar https://en.wikipedia.org/wiki/ESolar So... that part of the eSolar approach is carrying over into Heliogen. Last time this was posted the “AI” component of the play was less clear... But with an array of mirrors, in particular being to generate heat in some volume I guess a more complex feedback/control system may be required.

s_Hogg 7y ago
Are we talking about PIMCO Bill Gross here? If so, how did he wind up doing this?
- arethuza 7y ago
  Different Bill Gross: https://en.wikipedia.org/wiki/Bill_T._Gross https://en.wikipedia.org/wiki/Bill_T._Gross
ReptileMan 7y ago
What exactly do you need AI for except for buzzwording? It is not as if the sun/earth trajectory or rotation speed is random. You can precalc with ease at every point which is the best position for each mirror.
- viraptor 7y ago
  That did strike me as weird. Although they say "advanced computer vision software" so maybe they do some workaround and take the position from a camera rather than pre-calculations? Can it be the case that a few thousandths of a degree matters here and that's beyond our generalised model?
  - TeMPOraL 7y ago
    I'd imagine that the "few thousandths of a degree" is something you'd get worse with AI than with a mathematical model. AI methods introduce noise; with an explicit model you can keep adding complexity directly, until it gets more accurate than your measuring system. I suspect that the "AI" they mention is mostly photogrammetry - being able to tell the position and orientation of your mirrors from a video stream - in a feedback loop with motor controllers and temperature sensors. Use of cameras would make it close enough to "AI" that the buzzword would stick.
    - ovi256 7y ago
      >mostly photogrammetry - being able to tell the position and orientation of your mirrors from a video stream - in a feedback loop with motor controllers and temperature sensors. This. Modern photogrammetry uses computer vision techniques like deep neural nets. It's an amazing advancement. Imagine this problem: having to place a ground vehicle like a wheeled robot at an arbitrary coordinate in a room. The mirror positioning problem can be reduced to this one. Traditionally, you'd do it by building a very nice wheeled robot with non-slip wheels, wheel rotation angle sensors, fraction of a degree stepper motors, all very nice to work with, precise, and expensive. You could even solve this in an open-loop system with good enough actuators. Today, just stick a camera on the ceiling - or on the robot, if want a more challenging problem - and use CV to move a cheap RC car where you want. The Terminator will jangle and jiggle, instead of being built like a precise Swiss watch. But you'll get ten of them for the same price!
      - TeMPOraL 7y ago
        > This. Modern photogrammetry uses computer vision techniques like deep neural nets. I'm surprised to hear that. What good do DNN do for photogrammetry? Aren't they too unreliable? I only have university course-level exposure to this, most of it spent learning how to compute coordinate systems and transformation matrices from points on a set of pictures taken from different position. I guess DNNs could help with object isolation and labeling (identifying same objects on a set of pictures taken from different perspective)?
- truculent 7y ago
  Perhaps weather/clouds/objects are a thing that must be adapted to?
  - kuu 7y ago
    I guess this and also the lack of needing to make a detailed study about the sun position wherever the plant is established.
- new299 7y ago
  I would imagine that it’s not the suns location that is the primary concern, but where you are directing the light. The light is being reflected and focused by mirrors. That light is being directly onto some volume of material. So, in this case, they want to get the material above some critical temperature (e.g. so it melts). I imagine that uniformly heating the whole volume may not be the best approach, or that you may be able to work with smaller volumes depending on your expected solar input etc. So I can see a little more justification here than the case where solar cells are just being pointed at the sun.
- pjc50 7y ago
  The difficult problem is not knowing where the sun is but knowing where the ground is. Since all the panels are separate structures not on a single rigid slab, ground "settling" can tilt them fractionally in unpredictable ways. It sounds like what they have is machine vision as a novel input into a conventional control loop. For one panel at a time, wiggle it about and look how the light spot changes. Find the local maximum for tightest spot. That's now "locked" in the PLL sense and should stay locked for days or weeks.
  - JshWright 7y ago
    From my comfy armchair, with zero experience in this field, it seems like you could use star tracking to very accurately predict the angle of the sun (since the sun is effectively fixed in position relative to the background stars over the timescales you'd care about). Spotting the target is a little harder, but the same measurement could be made by sticking some reflectors in known positions around the target. I'm sure there are tons of considerations that aren't occurring to me (for instance, thermal expansion likely contributes substantially to making it a moving target (literally)), but I really don't see where "AI" comes into it...
    - smueller1234 7y ago
      Many years ago, I implemented star tracking for telescope alignment for auger.org. An actual basic version using libnova et al was pretty straightforward and a matter of days to prototype if I recall correctly (it was a project for a master student, so I had to do most of the work over a longer period of time). I think the accuracy was around a decimal fraction of a degree then. But the cameras of that thing have only 440 1.5° pixels (photomultipliers that sample at 5-20M samples/s). A higher resolution camera could probably do much better assuming you have a very accurate computer model of the optical properties of your telescope/lenses/camera.
    - dreamcompiler 7y ago
      Figuring out the sun's location is the easiest part of the problem. The hard part is that each mirror is a big, floppy slab that moves with wind, temperature, gear backlash, mechanical wear, rain/hail, and ground settling. The so-called "AI" here is really just a clever way to use closed-loop control so that the above factors don't matter much. (Side note: A large amount of "AI" these days just amounts to changing open-loop mechanisms to closed-loop, often by using computer vision as the state sensor. 3D printers, for example could become much more precise with no mechanical improvements if they did this. Probably some have already done so.)
- ovi256 7y ago
  Yes, you can precalc, and then you need very precise actuators to move the mirror to that precalced position. You also need precise surveying of the ground site to know its geometry. The precise actuators and surverying are expensive. Their approach is using cheap actuators in a closed-loop system where a computer vision controller (using the four cameras on top of the tower) moves the mirrors until it gets it right. Cheap actuator slip and lag is terrible, but with the feedback of the closed-loop, it's doable. This is an approach that's now allowing hobbyists to build cheaper motorised telescopes, robot arms and so on.

by new299 7y ago

s_Hogg 7y ago

Are we talking about PIMCO Bill Gross here? If so, how did he wind up doing this?

arethuza 7y ago
Different Bill Gross: https://en.wikipedia.org/wiki/Bill_T._Gross https://en.wikipedia.org/wiki/Bill_T._Gross

ReptileMan 7y ago

What exactly do you need AI for except for buzzwording? It is not as if the sun/earth trajectory or rotation speed is random. You can precalc with ease at every point which is the best position for each mirror.

viraptor 7y ago
That did strike me as weird. Although they say "advanced computer vision software" so maybe they do some workaround and take the position from a camera rather than pre-calculations? Can it be the case that a few thousandths of a degree matters here and that's beyond our generalised model?
- TeMPOraL 7y ago
  I'd imagine that the "few thousandths of a degree" is something you'd get worse with AI than with a mathematical model. AI methods introduce noise; with an explicit model you can keep adding complexity directly, until it gets more accurate than your measuring system. I suspect that the "AI" they mention is mostly photogrammetry - being able to tell the position and orientation of your mirrors from a video stream - in a feedback loop with motor controllers and temperature sensors. Use of cameras would make it close enough to "AI" that the buzzword would stick.
  - ovi256 7y ago
    >mostly photogrammetry - being able to tell the position and orientation of your mirrors from a video stream - in a feedback loop with motor controllers and temperature sensors. This. Modern photogrammetry uses computer vision techniques like deep neural nets. It's an amazing advancement. Imagine this problem: having to place a ground vehicle like a wheeled robot at an arbitrary coordinate in a room. The mirror positioning problem can be reduced to this one. Traditionally, you'd do it by building a very nice wheeled robot with non-slip wheels, wheel rotation angle sensors, fraction of a degree stepper motors, all very nice to work with, precise, and expensive. You could even solve this in an open-loop system with good enough actuators. Today, just stick a camera on the ceiling - or on the robot, if want a more challenging problem - and use CV to move a cheap RC car where you want. The Terminator will jangle and jiggle, instead of being built like a precise Swiss watch. But you'll get ten of them for the same price!
    - TeMPOraL 7y ago
      > This. Modern photogrammetry uses computer vision techniques like deep neural nets. I'm surprised to hear that. What good do DNN do for photogrammetry? Aren't they too unreliable? I only have university course-level exposure to this, most of it spent learning how to compute coordinate systems and transformation matrices from points on a set of pictures taken from different position. I guess DNNs could help with object isolation and labeling (identifying same objects on a set of pictures taken from different perspective)?
truculent 7y ago
Perhaps weather/clouds/objects are a thing that must be adapted to?
- kuu 7y ago
  I guess this and also the lack of needing to make a detailed study about the sun position wherever the plant is established.
new299 7y ago
I would imagine that it’s not the suns location that is the primary concern, but where you are directing the light. The light is being reflected and focused by mirrors. That light is being directly onto some volume of material. So, in this case, they want to get the material above some critical temperature (e.g. so it melts). I imagine that uniformly heating the whole volume may not be the best approach, or that you may be able to work with smaller volumes depending on your expected solar input etc. So I can see a little more justification here than the case where solar cells are just being pointed at the sun.
pjc50 7y ago
The difficult problem is not knowing where the sun is but knowing where the ground is. Since all the panels are separate structures not on a single rigid slab, ground "settling" can tilt them fractionally in unpredictable ways. It sounds like what they have is machine vision as a novel input into a conventional control loop. For one panel at a time, wiggle it about and look how the light spot changes. Find the local maximum for tightest spot. That's now "locked" in the PLL sense and should stay locked for days or weeks.
- JshWright 7y ago
  From my comfy armchair, with zero experience in this field, it seems like you could use star tracking to very accurately predict the angle of the sun (since the sun is effectively fixed in position relative to the background stars over the timescales you'd care about). Spotting the target is a little harder, but the same measurement could be made by sticking some reflectors in known positions around the target. I'm sure there are tons of considerations that aren't occurring to me (for instance, thermal expansion likely contributes substantially to making it a moving target (literally)), but I really don't see where "AI" comes into it...
  - smueller1234 7y ago
    Many years ago, I implemented star tracking for telescope alignment for auger.org. An actual basic version using libnova et al was pretty straightforward and a matter of days to prototype if I recall correctly (it was a project for a master student, so I had to do most of the work over a longer period of time). I think the accuracy was around a decimal fraction of a degree then. But the cameras of that thing have only 440 1.5° pixels (photomultipliers that sample at 5-20M samples/s). A higher resolution camera could probably do much better assuming you have a very accurate computer model of the optical properties of your telescope/lenses/camera.
  - dreamcompiler 7y ago
    Figuring out the sun's location is the easiest part of the problem. The hard part is that each mirror is a big, floppy slab that moves with wind, temperature, gear backlash, mechanical wear, rain/hail, and ground settling. The so-called "AI" here is really just a clever way to use closed-loop control so that the above factors don't matter much. (Side note: A large amount of "AI" these days just amounts to changing open-loop mechanisms to closed-loop, often by using computer vision as the state sensor. 3D printers, for example could become much more precise with no mechanical improvements if they did this. Probably some have already done so.)
ovi256 7y ago
Yes, you can precalc, and then you need very precise actuators to move the mirror to that precalced position. You also need precise surveying of the ground site to know its geometry. The precise actuators and surverying are expensive. Their approach is using cheap actuators in a closed-loop system where a computer vision controller (using the four cameras on top of the tower) moves the mirrors until it gets it right. Cheap actuator slip and lag is terrible, but with the feedback of the closed-loop, it's doable. This is an approach that's now allowing hobbyists to build cheaper motorised telescopes, robot arms and so on.