ToddlerBot · published recipe
bimanual manipulation (diffusion policy)
Record
- Robot
- ToddlerBot stanford/toddlerbot
- Framework
- Diffusion Policy (PyTorch) · PyTorch
- Policy license
- not stated by the package · robot software repos: MIT
- File
- toddlerbot/policies/dp_policy.py
- Note
- Expects results/<robot>_<task>_dp_<ckpt>/best_ckpt.pth from your own teleop data; no DP weights are published.
Not in the tab yet
To replay this policy in the browser we need an ONNX export of a trained checkpoint, the observation and action contract copied from the authors' own sim2sim or deploy script, and a MuJoCo model of the robot that the contract matches. Then it must walk 60 s in our runtime without a fall. Until then the source link is the way in.
Other ToddlerBot policies · 8
- walk (omnidirectional, 2XC)MuJoCo MJX + RSL-RL PPO, ONNX Runtime on Jetson
- get up from the groundMuJoCo MJX + RSL-RL PPO
- crawl (full / only / rotate)MuJoCo MJX + RSL-RL PPO
- crawl up / down stairsMuJoCo MJX + RSL-RL PPO
- climb up / down box, climb wallMuJoCo MJX + RSL-RL PPO
- multi-skill whole-body locomotion (Locomotion Beyond Feet)RL skill policies + depth skill classifier (FoundationStereo)
- push-up (keyframe replay)open-loop keyframe replay (run_policy.py --policy replay)
- cartwheel (DeepMimic-style)MuJoCo MJX + RSL-RL PPO