Add Aloha env and ACT policy

WIP Aloha env tests pass

Rendering works (fps look fast tho? TODO action bounding is too wide [-1,1])

Update README

Copy past from act repo

Remove download.py add a WIP for Simxarm

Remove download.py add a WIP for Simxarm

Add act yaml (TODO: try train.py)

Training can runs (TODO: eval)

Add tasks without end_effector that are compatible with dataset, Eval can run (TODO: training and pretrained model)

Add AbstractEnv, Refactor AlohaEnv, Add rendering_hook in env, Minor modifications, (TODO: Refactor Pusht and Simxarm)

poetry lock

fix bug in compute_stats for action normalization

fix more bugs in normalization

fix training

fix import

PushtEnv inheriates AbstractEnv, Improve factory Normalization

Add _make_env to EnvAbstract

Add call_rendering_hooks to pusht env

SimxarmEnv inherites from AbstractEnv (NOT TESTED)

Add aloha tests artifacts + update pusht stats

fix image normalization: before env was in [0,1] but dataset in [0,255], and now both in [0,255]

Small fix on simxarm

Add next to obs

Add top camera to Aloha env (TODO: make it compatible with set of cameras)

Add top camera to Aloha env (TODO: make it compatible with set of cameras)

README.md

@@ -59,19 +59,10 @@ env=pusht
 
 ## TODO
 
-- [x] priority update doesn't match FOWM or original paper
-- [x] self.step=100000 should be updated at every step to adjust to the horizon of the planner
-- [ ] prefetch replay buffer to speedup training
-- [ ] parallelize env to speed up eval
-- [ ] clean checkpointing / loading
-- [ ] clean logging
-- [ ] clean config
-- [ ] clean hyperparameter tuning
-- [ ] add pusht
-- [ ] add aloha
-- [ ] add act
-- [ ] add diffusion
-- [ ] add aloha 2
+If you are not sure how to contribute or want to know the next features we working on, look on this project page: [LeRobot TODO](https://github.com/users/Cadene/projects/1)
+
+Ask [Remi Cadene](re.cadene@gmail.com) for access if needed.
+
 
 ## Profile