Skip to main content

LocoFormer

Project description

LocoFormer (wip)

LocoFormer - Generalist Locomotion via Long-Context Adaptation

The gist is they trained a simple Transformer-XL in simulation on robots with many different bodies (cross-embodiment) and extreme domain randomization. When transferring to the real-world, they noticed the robot now gains the ability to adapt to insults. The XL memories span across multiple trials, which allowed the robot to learn in-context adaptation.

Sponsors

This open sourced work is sponsored by Safe Sentinel

Citations

@article{liu2025locoformer,
    title   = {LocoFormer: Generalist Locomotion via Long-Context Adaptation},
    author  = {Liu, Min and Pathak, Deepak and Agarwal, Ananye},
    journal = {Conference on Robot Learning ({CoRL})},
    year    = {2025}
}

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

locoformer-0.0.24.tar.gz (36.9 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

locoformer-0.0.24-py3-none-any.whl (10.9 kB view details)

Uploaded Python 3

File details

Details for the file locoformer-0.0.24.tar.gz.

File metadata

  • Download URL: locoformer-0.0.24.tar.gz
  • Upload date:
  • Size: 36.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for locoformer-0.0.24.tar.gz
Algorithm Hash digest
SHA256 9775efa79b660439cdce9ab073bde27997de6d8b5e34681f8ce5d94721e0109f
MD5 541c888ae9e86bcd7465872c72207f94
BLAKE2b-256 1a27b63410c28680b213ce6f3b4fa6f0483ee7c8908cca2a0b57a939606f23e1

See more details on using hashes here.

File details

Details for the file locoformer-0.0.24-py3-none-any.whl.

File metadata

  • Download URL: locoformer-0.0.24-py3-none-any.whl
  • Upload date:
  • Size: 10.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for locoformer-0.0.24-py3-none-any.whl
Algorithm Hash digest
SHA256 ea52a1b52677a1e09f76baf68285c5c502ba7ca90413303e87f3eff6ec66aabd
MD5 e02c4bce3aa2dc256d338e69c35fbf98
BLAKE2b-256 600592c934da02f7f01c268bd0449cebb8cf6988d4348a7ca87b237f15e98d1a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page