Release v0.5.0

.gitignore

@@ -74,6 +74,7 @@ outputs/
 benchmark_results/
 logs/
 ckpt/
+ckpt_restore/
 wandb/
 *.log
 # Training - downloaded reference assets (re-downloadable)

CHANGELOG.md

@@ -1,5 +1,19 @@
 # Changelog
 
+## [0.5.0] - 2026-08-03
+
+- 新增独立的 host high-level-policy sim2real 运行时：使用严格的 msgpack/ZeroMQ 协议、异步 receding-horizon replanning、时间戳对齐调度，以及 50 Hz 输出安全校验和限速。
+- 扩展 G1 外设支持：加入 OpenNeck 0.2.0 物理角度控制、Pico HMD 主动视觉映射、LinkerHand O6 somehand 0.3.0 手势控制，以及手部和颈部状态回读。
+- 更新 sim2real 录制与审阅流程：采用 `schema.json`、`episodes.jsonl`、逐 episode HDF5 和压缩 MP4 布局，记录可选手部/颈部状态与动作，并新增同步 recording viewer。
+- 新增匹配的 G1 模型/策略组合：默认 `g1_29dof.xml` 配合 `ckpt/track_g1.{pt,onnx}`，neck-and-O6 版本配合 `g1_29dof_neck_o6.xml` 和 `ckpt/track_g1_neck_o6.{pt,onnx}`。
+- 更新 OmniXtreme-style benchmark，并增强 Pico/RealSense 故障恢复、GMR mocap-entry cold start、high-level-policy watchdog 和引用安全处理。
+
+### 迁移说明
+
+- v0.4 的根目录 `track.{pt,onnx}` 路径已替换为 `ckpt/track_g1.{pt,onnx}`；neck-and-O6 运行时必须使用对应的模型和策略组合。
+- 旧的 attribute-based sim2real HDF5 格式不再支持；录制、转换和审阅工具使用当前 manifest-based source layout。
+- Host-policy 网络协议不提供旧 envelope 兼容，OpenNeck 旧 normalized API 也不再支持；Teleopit 与 companion runtime 必须使用匹配版本。
+
 ## [0.4.0] - 2026-06-25
 
 - 改进 Pico 实时控制：支持 pico-bridge 0.2.1、`ARMS` 模式，以及保留 retargeter warm-start 的模式切换/暂停恢复。

README.md

@@ -1,5 +1,5 @@
 <p align="center">
-  <img src="assets/teleopit_logo.jpg" width="80" alt="Teleopit">
+  <img src="assets/teleopit.png" width="720" alt="Teleopit whole-body teleoperation demo">
 </p>
 
 <h1 align="center">Teleopit</h1>
@@ -11,11 +11,9 @@
 </p>
 
 <p align="center">
+  <a href="https://botrunner64.github.io/teleopit-page/">Project Homepage</a> &bull;
   <a href="https://BotRunner64.github.io/Teleopit/">Documentation</a> &bull;
-  <a href="https://BotRunner64.github.io/Teleopit/zh-Hans/">中文文档</a> &bull;
-  <a href="https://BotRunner64.github.io/Teleopit/tutorials/pico-sim2sim">Pico Sim2Sim</a> &bull;
-  <a href="https://BotRunner64.github.io/Teleopit/tutorials/pico-sim2real">Pico Sim2Real</a> &bull;
-  <a href="https://BotRunner64.github.io/Teleopit/tutorials/training">Training</a>
+  <a href="https://BotRunner64.github.io/Teleopit/zh-Hans/">中文文档</a>
 </p>
 
 ---
@@ -35,15 +33,18 @@ pip install modelscope
 python scripts/setup/download_assets.py --only robots gmr ckpt bvh
 ```
 
-The canonical Unitree G1 robot model is downloaded to
-`assets/robots/unitree_g1/g1_29dof.xml`. Training, sim2sim, retargeting, and FK
-validation all use this same XML.
+The default Unitree G1 robot model is downloaded to
+`assets/robots/unitree_g1/g1_29dof.xml`, with additional model variants in the
+same directory. Training can select a task-compatible XML with `--robot_xml`;
+the quick-start command below uses the default model and its matching
+`ckpt/track_g1.onnx` policy. The neck-and-O6 variant uses
+`g1_29dof_neck_o6.xml` with `ckpt/track_g1_neck_o6.onnx`.
 
 **3. Run**
 
 ```bash
 python scripts/run/run_sim.py \
-    controller.policy_path=track.onnx \
+    controller.policy_path=ckpt/track_g1.onnx \
     input.bvh_file=data/sample_bvh/aiming1_subject1.bvh
 ```
 
@@ -53,71 +54,38 @@ To show the simulated D435i RGB camera view, add the explicit `camera` viewer:
 
 ```bash
 python scripts/run/run_sim.py \
-    controller.policy_path=track.onnx \
+    controller.policy_path=ckpt/track_g1.onnx \
     input.bvh_file=data/sample_bvh/aiming1_subject1.bvh \
     'viewers=[sim2sim,camera]'
 ```
 
 For sim2real, viewers are disabled by default. Add `viewers=retarget` to show
 the retargeted reference in an optional MuJoCo window.
 
-## Pico Motion Recording
-
-Record many Pico clips as training-ready G1 motion NPZ files:
-
-```bash
-pip install -e '.[pico4]'
-python scripts/run/record_pico_motion.py
-```
-
-The recorder starts the Pico receiver and live Retarget viewer before waiting
-for clip names, so preview keeps running while the terminal is idle. Enter a
-semantic clip name, then use `R` to start, `S` to save, `D` to discard, `N` for
-a new name, and `Q` to quit. Saved clips are written to
-`data/pico_motion/clips/` using the semantic label in the filename, with no
-sidecar JSON.
-
-Merge recorded clips into the standard HDF5 shard dataset:
-
-```bash
-python train_mimic/scripts/data/build_dataset.py \
-    --spec data/pico_motion/pico_recorded.yaml --force
-```
-
-## Sim2Real HDF5 Recording
+## Documentation
 
-Pico sim2real can also record manual HDF5 episodes from the real G1:
+Full docs at **[BotRunner64.github.io/Teleopit](https://BotRunner64.github.io/Teleopit/)**, covering installation profiles, all tutorials, configuration reference, and architecture.
 
-```bash
-pip install -e '.[recording]'
-# If you use RealSense video, install pyrealsense2 manually for your platform.
-# On Arm machines, prefer conda-forge:
-# conda install -c conda-forge pyrealsense2
-python scripts/run/run_sim2real.py --config-name sim2real_record \
-    controller.policy_path=track.onnx \
-    recording.task="walk forward"
-```
+## Changelog
 
-Recording uses the terminal controls `R` start, `S` save, `D` discard, and `Q`
-shutdown. `STANDING`, `MOCAP`, `ARMS`, and paused mocap can be recorded. Saved
-episodes are written as `.h5` files under `data/recordings/sim2real_hdf5/episodes/`.
-`sim2real_record.yaml` stores camera frames as compressed MP4 sidecar files under
-`data/recordings/sim2real_hdf5/videos/` and keeps `frame_index` / `timestamp`
-sync metadata in the HDF5 episode. The low-dimensional HDF5 schema records
-`observation.state(68)`, `observation.mode(1)`, `action(36)` as the aligned
-reference qpos sent to the policy path, and `action.hand(12)` as the latest
-LinkerHand left/right 6D pose commands.
+### v0.5.0 (2026-08-03)
 
-## Documentation
+- Added an independent host high-level-policy sim2real runtime with a strict msgpack/ZeroMQ protocol, asynchronous receding-horizon replanning, timestamp-aligned scheduling, and validated, rate-limited 50 Hz output.
+- Extended G1 peripheral support with OpenNeck 0.2.0 physical-angle control, Pico HMD active-vision mapping, LinkerHand O6 hand-pose control through somehand 0.3.0, and hand/neck state readback.
+- Updated sim2real recording and review around `schema.json`, `episodes.jsonl`, per-episode HDF5 files, compressed MP4 video, optional hand/neck state and action fields, and a synchronized recording viewer.
+- Added matched G1 model/policy pairs: `g1_29dof.xml` with `ckpt/track_g1.{pt,onnx}`, and `g1_29dof_neck_o6.xml` with `ckpt/track_g1_neck_o6.{pt,onnx}`.
+- Updated the OmniXtreme-style benchmark and hardened Pico/RealSense recovery, GMR mocap-entry cold start, the high-level-policy watchdog, and reference safety handling.
 
-Full docs at **[BotRunner64.github.io/Teleopit](https://BotRunner64.github.io/Teleopit/)**, covering installation profiles, all tutorials, configuration reference, and architecture.
+#### Migration notes
 
-## Changelog
+- The v0.4 root-level `track.{pt,onnx}` paths are replaced by `ckpt/track_g1.{pt,onnx}`; the neck-and-O6 runtime requires its matching robot model and policy.
+- The old attribute-based sim2real HDF5 format is unsupported; recording, conversion, and review use the current manifest-based source layout.
+- The host-policy protocol has no legacy envelope compatibility, and the old normalized OpenNeck API is unsupported; Teleopit and its companion runtimes must use matching versions.
 
 ### v0.4.0 (2026-06-25)
 
 - Improved Pico realtime control with pico-bridge 0.2.1, `ARMS` mode, armed sim2real mocap entry, and retargeter-preserving pause/arms resets.
-- Added optional LinkerHand L6/O6 sim2real control, including Pico gripper input and low-latency L6 `vr_hand_pose`.
+- Added optional LinkerHand L6/O6 sim2real control, including Pico gripper input and low-latency L6/O6 `vr_hand_pose`.
 - Added manual Pico sim2real HDF5 recording and an interactive Pico motion recorder for training NPZ clips.
 - Refined the training data path with minimal HDF5 shards, explicit precompute, rewind sampling, and updated tracking rewards.