Humanoid robots are much more difficult than non-humanoid ones. There are a lot more joints than in other designs; the balance question demands both more capable components and more advanced controls; as a consequence of the balance and shape questions, a lot of thought needs to go into wrangling weight ratios, which means preferring more expensive materials for lightness, etc.
In terms of modifying your analysis, I think this cashes out as greater material intensity—the calculations here are done by weight of materials, we just need a way to account for the humanoid robot requiring more processing on all of those materials. We could say something like 1500kg of humanoid robot materials take twice as much processing/refinement as 1500kg of car materials (occasionally this will be about the same; for small fractions of the weight it will be 10x the processing, etc).
The humanoid robots are more vulnerable to bottlenecks than cars. Specifically they need more compute and rare earth elements like neodymium, which will be tough because that supply chain is already strained by new datacenters and AI demands.
I’m especially keen to explore bottlenecks (e.g. another suggestion I saw is that to reach 1 billion a year would require 10x current global lithium production to supply the batteries.)
A factor of 2 for increased difficultly due to processing intensity seems reasonable, and I should have thrown it in. (Though my estimates were to an order of magnitude so this probably won’t change the bottom line, and on the other side, many robots will weigh <100kg and some will be non-humanoid.)
I like this effort, and I have a few suggestions:
Humanoid robots are much more difficult than non-humanoid ones. There are a lot more joints than in other designs; the balance question demands both more capable components and more advanced controls; as a consequence of the balance and shape questions, a lot of thought needs to go into wrangling weight ratios, which means preferring more expensive materials for lightness, etc.
In terms of modifying your analysis, I think this cashes out as greater material intensity—the calculations here are done by weight of materials, we just need a way to account for the humanoid robot requiring more processing on all of those materials. We could say something like 1500kg of humanoid robot materials take twice as much processing/refinement as 1500kg of car materials (occasionally this will be about the same; for small fractions of the weight it will be 10x the processing, etc).
The humanoid robots are more vulnerable to bottlenecks than cars. Specifically they need more compute and rare earth elements like neodymium, which will be tough because that supply chain is already strained by new datacenters and AI demands.
Thanks for the comments!
I’m especially keen to explore bottlenecks (e.g. another suggestion I saw is that to reach 1 billion a year would require 10x current global lithium production to supply the batteries.)
A factor of 2 for increased difficultly due to processing intensity seems reasonable, and I should have thrown it in. (Though my estimates were to an order of magnitude so this probably won’t change the bottom line, and on the other side, many robots will weigh <100kg and some will be non-humanoid.)