Relocalization algo has standard components but heavily depends on embodiment, sensor and sensor mounting spot.
We need a ready to go autoresearch package to run on collected datasets for each sensor style. Keep in mind relocalization is stohastic and chaotic, autoresearch eval needs to be deterministic in order for improvements to be noticable and not random (we had to peg a bunch of random seeds and run a process (not a thread) per core)
#2137
Refactor relocalization into an easy to use chainable toolset (ala streams) with tunable hyperparams per processing step
Potentially run an actual classical search on hyperparams before handing off to autotune
(mention in instructions that people shouldn't evaluate relocalization based on the same dataset the relocalization target map was built fromm)
Relocalization algo has standard components but heavily depends on embodiment, sensor and sensor mounting spot.
We need a ready to go autoresearch package to run on collected datasets for each sensor style. Keep in mind relocalization is stohastic and chaotic, autoresearch eval needs to be deterministic in order for improvements to be noticable and not random (we had to peg a bunch of random seeds and run a process (not a thread) per core)
#2137
Refactor relocalization into an easy to use chainable toolset (ala streams) with tunable hyperparams per processing step
Potentially run an actual classical search on hyperparams before handing off to autotune
(mention in instructions that people shouldn't evaluate relocalization based on the same dataset the relocalization target map was built fromm)