We’ve gone a totally different way, but this is another interesting project from Erwin Coumans, on the Google Brain team, who did PyBullet. NeuralSim replaces parts of physics engines with neural networks.
https://sites.google.com/usc.edu/neuralsim
https://github.com/google-research/tiny-differentiable-simulator
Another MIT group: The MCube Lab. Some grasping datasets and such. Looks like a good resource.
The Egg-Tech Prize and Phase 1 winners
Taken from https://foundationfar.org/grants-funding/opportunities/egg-tech-prize/
Interesting as a guideline for comparison with international efforts, and for perspective of the sort of money in this problem. “the industry could save between $1.5 billion and $2.5 billion each year.” – News Article.
The Egg-Tech Prize Phase II criteria forms the basis for the merit-based review, outlined above.
Day and potential to utilize male eggs (up to 25 points).
Minimum: Functions on or before day 8 of incubation. Preference for solutions with reduced incubation time with pre-incubation most preferred. Protocols involving short periods of incubation during egg storage (SPIODES) will be considered preincubation and given preference. Preference will be given to technologies that enable the use of male eggs in other applications.
Accuracy (up to 20 points).
Minimum: 98 percent accuracy. Preference will be given to technologies that work with all chicken breeds/colors commonly used in commercial production.
Economic Feasibility (up to 20 points).
Score for this criterion will consider economic feasibility based on a cost-benefit analysis and business plan that should include:
Direct costs:
Indirect costs:
Predicted revenues gained for hatchery in diverting eggs, energy savings, labor, cost-savings from not feeding male chicks (depending on country), etc.
Throughput and physical size (up to 15 points)
Potential for sexing at least 15,000 eggs per hour (more preferred). If multiple units will be used in combination to achieve the desired throughput, only one demonstration unit will be required but all units needed to meet the desired throughput must fit into existing hatchery structures, with reasonable and appropriate modifications.
Hatchability (up to 15 points)
Minimum: Does not reduce hatching rate by more than 1.5 percent from baseline.
Speed of test results (up to 5 points)
Results returned in less than 30 min if eggs are tested during incubation (allowable time for removal, testing and return to incubator).† If eggs are tested prior to incubation, with or without SPIDES, results must be available within 48 hours of testing. Accurate tracking and identification of eggs must be demonstrated.
†Longer times until test result will require placing eggs back into the incubator, in which case they must be removed again for sorting.
Came across a ‘non-partisan’ group, with a github archive of RL links. It’s pretty epic.
https://www.nature.com/articles/nature14422 and MAP-Elites algorithm: https://www.researchgate.net/publication/277323278_Robots_that_can_adapt_like_animals
https://github.com/benureau/recode/tree/master/cully2015
https://github.com/resibots/ite_v2
http://www.cs.uvm.edu/~jbongard/papers/2014_PLOSCompBio_Auerbach.pdf
very cool: http://eplex.cs.ucf.edu/ecal13/demo/PCA.html?uid=192750
https://www.creativemachineslab.com/