deployment workspace for ViBe trackers to unitree_mujoco and the Unitree G1 hardware
nvidia-smi)From a fresh shell:
git clone https://github.com/drcl-deploy/vibe_ws
cd vibe_ws
./install.sh --system # fetch, generate scenes, build
[!NOTE] For custom models, use absolute paths or place it under
artifacts/.
Run from the workspace root in each terminal, with a gamepad connected.
# terminal 1: simulator
sample=walk # walk | parkour | repose | uolm
./unitree_mujoco/simulate/build/unitree_mujoco \
-s "$PWD/generated/$sample/scene.xml"
# terminal 2: encoder + tracker
source setup_local.sh
sample=walk # walk | parkour | repose | uolm
ros2 launch cpp_control g1_vibe_sonic.launch.py \
policy_path:="models/$sample/policy.onnx" \
encoder_path:=encoders/theia-tiny.onnx \
motion_path:="$PWD/data/sample/$sample/motion.npz"
sample in both terminals; the scene, motion and policy follow it.| Sample | Demo |
|---|---|
walk | Grail curbs |
parkour | OmRe climb |
repose | Double cube frontflip |
uolm | Suitcase |
# terminal 1: simulator + cube
./unitree_mujoco/simulate/build/unitree_mujoco \
-s "$PWD/generated/repose/g1_repose.xml"
# terminal 2: encoder + tracker
source setup_local.sh
ros2 launch cpp_control g1_vibe_sonic.launch.py \
policy_path:=models/repose/policy.onnx \
encoder_path:=encoders/theia-tiny.onnx \
planner:=true \
stand_yaw_teleop:=true stand_walk_teleop:=true \
stand_walk_motion:="$PWD/cyclonedds_ws/install/sledgehammer/share/sledgehammer/data/sys1_walk/walk_forward_amateur_001__A001/motion.npz"
# terminal 3: planner + console
source setup_local.sh
ros2 launch sledgehammer planner.launch.py env:=sim
to visualize the learnt attention maps , run in another terminal:
source setup_local.sh
bash cyclonedds_ws/src/cpp_control/scripts/vibe/stream_vibes.sh
deployment workspace for ViBe trackers to unitree_mujoco and the Unitree G1 hardware
nvidia-smi)From a fresh shell:
git clone https://github.com/drcl-deploy/vibe_ws
cd vibe_ws
./install.sh --system # fetch, generate scenes, build
[!NOTE] For custom models, use absolute paths or place it under
artifacts/.
Run from the workspace root in each terminal, with a gamepad connected.
# terminal 1: simulator
sample=walk # walk | parkour | repose | uolm
./unitree_mujoco/simulate/build/unitree_mujoco \
-s "$PWD/generated/$sample/scene.xml"
# terminal 2: encoder + tracker
source setup_local.sh
sample=walk # walk | parkour | repose | uolm
ros2 launch cpp_control g1_vibe_sonic.launch.py \
policy_path:="models/$sample/policy.onnx" \
encoder_path:=encoders/theia-tiny.onnx \
motion_path:="$PWD/data/sample/$sample/motion.npz"
sample in both terminals; the scene, motion and policy follow it.| Sample | Demo |
|---|---|
walk | Grail curbs |
parkour | OmRe climb |
repose | Double cube frontflip |
uolm | Suitcase |
# terminal 1: simulator + cube
./unitree_mujoco/simulate/build/unitree_mujoco \
-s "$PWD/generated/repose/g1_repose.xml"
# terminal 2: encoder + tracker
source setup_local.sh
ros2 launch cpp_control g1_vibe_sonic.launch.py \
policy_path:=models/repose/policy.onnx \
encoder_path:=encoders/theia-tiny.onnx \
planner:=true \
stand_yaw_teleop:=true stand_walk_teleop:=true \
stand_walk_motion:="$PWD/cyclonedds_ws/install/sledgehammer/share/sledgehammer/data/sys1_walk/walk_forward_amateur_001__A001/motion.npz"
# terminal 3: planner + console
source setup_local.sh
ros2 launch sledgehammer planner.launch.py env:=sim
to visualize the learnt attention maps , run in another terminal:
source setup_local.sh
bash cyclonedds_ws/src/cpp_control/scripts/vibe/stream_vibes.sh