README.md
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1 ---
2 license: mit
3 library_name: stable-baselines3
4 tags:
5 - reinforcement-learning
6 - robotics
7 - myosuite
8 - gymnasium
9 ---
10
11 # Joint-Space Empowerment for Dexterous Coordination in Tendon-Driven Hands
12
13 This repository contains the official trained policies for
14
15 > **Joint-Space Empowerment for Dexterous Coordination in Tendon-Driven Hands**
16 > *James Heald, Vittorio Caggiano, Vikash Kumar, Maneesh Sahani*
17 > **ICML 2026 (Spotlight)**
18 > [Paper](https://openreview.net/pdf?id=qI2eHwfNfh) | [Code](https://github.com/gatsby-sahani/JoSE) | [Project Page](https://joint-space-empowerment.github.io/)
19
20 ---
21
22 ## 📂 Repository Structure
23
24 The files are organized by task environment and training seed:
25
26 ```text
27 joint-space-empowerment
28 ├── Adroit
29 │ ├── BaodingBalls
30 │ │ ├── CustomAdroitBaodingP1-v1.yaml # Environment config
31 │ │ ├── seed_0
32 │ │ │ ├── rl_model_10000000_steps.zip # Trained model
33 │ │ │ └── rl_model_vecnormalize_10000000_steps.pkl # Observation normalization statistics
34 │ │ ├── seed_1 … seed_4
35 │ ├── DieReorient
36 │ │ └── ...
37 │ ├── KeyTurn
38 │ │ └── ...
39 │ └── PenTwirl
40 │ └── ...
41 ├── MyoHand
42 │ ├── BaodingBalls
43 │ │ └── ...
44 │ ├── DieReorient
45 │ │ └── ...
46 │ ├── KeyTurn
47 │ │ └── ...
48 │ ├── PenTwirl
49 │ │ └── ...
50 │ ├── Reorient100
51 │ │ ├── Pretraining_Play
52 │ │ │ ├── seed_0
53 │ │ │ │ ├── rl_model_replay_buffer_1000000_steps.pkl # Replay buffer
54 │ │ │ │ └── rl_model_vecnormalize_1000000_steps.pkl
55 │ │ │ ├── seed_1 … seed_4
56 │ │ └── Training
57 │ │ └── ...
58 │ └── Reorient8-sparse
59 │ └── ...
60 └── README.md
61 ```
62
63 ## Loading Example
64
65 > **Prerequisites:** clone and install the [JoSE repository](https://github.com/gatsby-sahani/JoSE).
66
67 The `play.py` script in the JoSE repository downloads a pretrained model and executes it in the corresponding environment, allowing agent behaviour to be visualized. The script is called from the repo root as follows:
68
69 ```bash
70 uv run python play.py --hand <hand> --task <task> --seed <seed>
71 ```
72
73 | Argument | Choices |
74 |---|---|
75 | `--hand` | `Adroit`, `MyoHand` |
76 | `--task` | `BaodingBalls`, `DieReorient`, `KeyTurn`, `PenTwirl`, `Reorient8-sparse`, `Reorient100/Training` |
77 | `--seed` | `0`, `1`, `2`, `3`, `4`, `5` |
78
79 Seeds vary by hand and task. See the HuggingFace model directory to see which seeds are available for each task-hand combination.
80