Merge remote-tracking branch 'origin/user/aliberts/2025_02_25_refactor_robots' into user/aliberts/2025_04_03_add_hope_jr

This commit is contained in:
Simon Alibert
2025-05-22 11:35:09 +02:00
17 changed files with 86 additions and 333 deletions

View File

@@ -1,68 +0,0 @@
{
"homing_offset": [
2048,
3072,
3072,
-1024,
-1024,
2048,
-2048,
2048,
-2048
],
"drive_mode": [
1,
1,
1,
0,
0,
1,
0,
1,
0
],
"start_pos": [
2015,
3058,
3061,
1071,
1071,
2035,
2152,
2029,
2499
],
"end_pos": [
-1008,
-1963,
-1966,
2141,
2143,
-971,
3043,
-1077,
3144
],
"calib_mode": [
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"LINEAR"
],
"motor_names": [
"waist",
"shoulder",
"shoulder_shadow",
"elbow",
"elbow_shadow",
"forearm_roll",
"wrist_angle",
"wrist_rotate",
"gripper"
]
}

View File

@@ -1,68 +0,0 @@
{
"homing_offset": [
2048,
3072,
3072,
-1024,
-1024,
2048,
-2048,
2048,
-1024
],
"drive_mode": [
1,
1,
1,
0,
0,
1,
0,
1,
0
],
"start_pos": [
2035,
3024,
3019,
979,
981,
1982,
2166,
2124,
1968
],
"end_pos": [
-990,
-2017,
-2015,
2078,
2076,
-1030,
3117,
-1016,
2556
],
"calib_mode": [
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"LINEAR"
],
"motor_names": [
"waist",
"shoulder",
"shoulder_shadow",
"elbow",
"elbow_shadow",
"forearm_roll",
"wrist_angle",
"wrist_rotate",
"gripper"
]
}

View File

@@ -1,68 +0,0 @@
{
"homing_offset": [
2048,
3072,
3072,
-1024,
-1024,
2048,
-2048,
2048,
-2048
],
"drive_mode": [
1,
1,
1,
0,
0,
1,
0,
1,
0
],
"start_pos": [
2056,
2895,
2896,
1191,
1190,
2018,
2051,
2056,
2509
],
"end_pos": [
-1040,
-2004,
-2006,
2126,
2127,
-1010,
3050,
-1117,
3143
],
"calib_mode": [
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"LINEAR"
],
"motor_names": [
"waist",
"shoulder",
"shoulder_shadow",
"elbow",
"elbow_shadow",
"forearm_roll",
"wrist_angle",
"wrist_rotate",
"gripper"
]
}

View File

@@ -1,68 +0,0 @@
{
"homing_offset": [
2048,
3072,
3072,
-1024,
-1024,
2048,
-2048,
2048,
-2048
],
"drive_mode": [
1,
1,
1,
0,
0,
1,
0,
1,
0
],
"start_pos": [
2068,
3034,
3030,
1038,
1041,
1991,
1948,
2090,
1985
],
"end_pos": [
-1025,
-2014,
-2015,
2058,
2060,
-955,
3091,
-940,
2576
],
"calib_mode": [
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"DEGREE",
"LINEAR"
],
"motor_names": [
"waist",
"shoulder",
"shoulder_shadow",
"elbow",
"elbow_shadow",
"forearm_roll",
"wrist_angle",
"wrist_rotate",
"gripper"
]
}

7
.gitignore vendored
View File

@@ -11,7 +11,10 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# Dev scripts
.dev
# Logging
logs
tmp
@@ -91,10 +94,8 @@ coverage.xml
.hypothesis/
.pytest_cache/
# Ignore .cache except calibration
# Ignore .cache
.cache/*
!.cache/calibration/
!.cache/calibration/**
# Translations
*.mo

View File

@@ -55,7 +55,7 @@ conda install ffmpeg -c conda-forge
Install 🤗 LeRobot:
```bash
cd lerobot && pip install ".[feetech]"
cd lerobot && pip install -e ".[feetech]"
```
## Troubleshooting

View File

@@ -142,7 +142,6 @@ from lerobot.common.datasets.video_utils import (
get_video_info,
)
from lerobot.common.robots import RobotConfig
from lerobot.common.robots.utils import make_robot_config
V16 = "v1.6"
V20 = "v2.0"
@@ -598,6 +597,30 @@ def convert_dataset(
create_branch(repo_id=repo_id, branch=V20, repo_type="dataset")
def make_robot_config(robot_type: str, **kwargs) -> RobotConfig:
if robot_type == "aloha":
raise NotImplementedError # TODO
elif robot_type == "koch_follower":
from lerobot.common.robots.koch_follower import KochFollowerConfig
return KochFollowerConfig(**kwargs)
elif robot_type == "so100_follower":
from lerobot.common.robots.so100_follower import SO100FollowerConfig
return SO100FollowerConfig(**kwargs)
elif robot_type == "stretch":
from lerobot.common.robots.stretch3 import Stretch3RobotConfig
return Stretch3RobotConfig(**kwargs)
elif robot_type == "lekiwi":
from lerobot.common.robots.lekiwi import LeKiwiConfig
return LeKiwiConfig(**kwargs)
else:
raise ValueError(f"Robot type '{robot_type}' is not available.")
def main():
parser = argparse.ArgumentParser()
task_args = parser.add_mutually_exclusive_group(required=True)

View File

@@ -32,7 +32,8 @@ class EnvConfig(draccus.ChoiceRegistry, abc.ABC):
def type(self) -> str:
return self.get_choice_name(self.__class__)
@abc.abstractproperty
@property
@abc.abstractmethod
def gym_kwargs(self) -> dict:
raise NotImplementedError()

View File

@@ -108,6 +108,7 @@ class DynamixelMotorsBus(MotorsBus):
https://emanual.robotis.com/docs/en/software/dynamixel/dynamixel_sdk/sample_code/python_read_write_protocol_2_0/#python-read-write-protocol-20
"""
apply_drive_mode = False
available_baudrates = deepcopy(AVAILABLE_BAUDRATES)
default_baudrate = DEFAULT_BAUDRATE
default_timeout = DEFAULT_TIMEOUT_MS

View File

@@ -102,6 +102,7 @@ class FeetechMotorsBus(MotorsBus):
python feetech sdk to communicate with the motors, which is itself based on the dynamixel sdk.
"""
apply_drive_mode = True
available_baudrates = deepcopy(SCAN_BAUDRATES)
default_baudrate = DEFAULT_BAUDRATE
default_timeout = DEFAULT_TIMEOUT_MS

View File

@@ -252,6 +252,7 @@ class MotorsBus(abc.ABC):
```
"""
apply_drive_mode: bool
available_baudrates: list[int]
default_baudrate: int
default_timeout: int
@@ -756,7 +757,7 @@ class MotorsBus(abc.ABC):
return mins, maxes
def _normalize(self, data_name: str, ids_values: dict[int, int]) -> dict[int, float]:
def _normalize(self, ids_values: dict[int, int]) -> dict[int, float]:
if not self.calibration:
raise RuntimeError(f"{self} has no calibration registered.")
@@ -765,20 +766,24 @@ class MotorsBus(abc.ABC):
motor = self._id_to_name(id_)
min_ = self.calibration[motor].range_min
max_ = self.calibration[motor].range_max
drive_mode = self.apply_drive_mode and self.calibration[motor].drive_mode
if max_ == min_:
raise ValueError(f"Invalid calibration for motor '{motor}': min and max are equal.")
bounded_val = min(max_, max(min_, val))
# TODO(Steven): normalization can go boom if max_ == min_, we should add a check probably in record_ranges_of_motions
# (which probably indicates the user forgot to move a motor, most likely a gripper-like one)
if self.motors[motor].norm_mode is MotorNormMode.RANGE_M100_100:
normalized_values[id_] = (((bounded_val - min_) / (max_ - min_)) * 200) - 100
norm = (((bounded_val - min_) / (max_ - min_)) * 200) - 100
normalized_values[id_] = -norm if drive_mode else norm
elif self.motors[motor].norm_mode is MotorNormMode.RANGE_0_100:
normalized_values[id_] = ((bounded_val - min_) / (max_ - min_)) * 100
norm = ((bounded_val - min_) / (max_ - min_)) * 100
normalized_values[id_] = 100 - norm if drive_mode else norm
else:
# TODO(alibers): velocity and degree modes
# TODO(alibers): degree mode
raise NotImplementedError
return normalized_values
def _unnormalize(self, data_name: str, ids_values: dict[int, float]) -> dict[int, int]:
def _unnormalize(self, ids_values: dict[int, float]) -> dict[int, int]:
if not self.calibration:
raise RuntimeError(f"{self} has no calibration registered.")
@@ -787,14 +792,20 @@ class MotorsBus(abc.ABC):
motor = self._id_to_name(id_)
min_ = self.calibration[motor].range_min
max_ = self.calibration[motor].range_max
drive_mode = self.apply_drive_mode and self.calibration[motor].drive_mode
if max_ == min_:
raise ValueError(f"Invalid calibration for motor '{motor}': min and max are equal.")
if self.motors[motor].norm_mode is MotorNormMode.RANGE_M100_100:
val = -val if drive_mode else val
bounded_val = min(100.0, max(-100.0, val))
unnormalized_values[id_] = int(((bounded_val + 100) / 200) * (max_ - min_) + min_)
elif self.motors[motor].norm_mode is MotorNormMode.RANGE_0_100:
val = 100 - val if drive_mode else val
bounded_val = min(100.0, max(0.0, val))
unnormalized_values[id_] = int((bounded_val / 100) * (max_ - min_) + min_)
else:
# TODO(alibers): velocity and degree modes
# TODO(aliberts): degree mode
raise NotImplementedError
return unnormalized_values
@@ -915,7 +926,7 @@ class MotorsBus(abc.ABC):
id_value = self._decode_sign(data_name, {id_: value})
if normalize and data_name in self.normalized_data:
id_value = self._normalize(data_name, id_value)
id_value = self._normalize(id_value)
return id_value[id_]
@@ -982,7 +993,7 @@ class MotorsBus(abc.ABC):
addr, length = get_address(self.model_ctrl_table, model, data_name)
if normalize and data_name in self.normalized_data:
value = self._unnormalize(data_name, {id_: value})[id_]
value = self._unnormalize({id_: value})[id_]
value = self._encode_sign(data_name, {id_: value})[id_]
@@ -1061,7 +1072,7 @@ class MotorsBus(abc.ABC):
ids_values = self._decode_sign(data_name, ids_values)
if normalize and data_name in self.normalized_data:
ids_values = self._normalize(data_name, ids_values)
ids_values = self._normalize(ids_values)
return {self._id_to_name(id_): value for id_, value in ids_values.items()}
@@ -1147,7 +1158,7 @@ class MotorsBus(abc.ABC):
addr, length = get_address(self.model_ctrl_table, model, data_name)
if normalize and data_name in self.normalized_data:
ids_values = self._unnormalize(data_name, ids_values)
ids_values = self._unnormalize(ids_values)
ids_values = self._encode_sign(data_name, ids_values)

View File

@@ -49,15 +49,18 @@ class Robot(abc.ABC):
return f"{self.id} {self.__class__.__name__}"
# TODO(aliberts): create a proper Feature class for this that links with datasets
@abc.abstractproperty
@property
@abc.abstractmethod
def observation_features(self) -> dict:
pass
@abc.abstractproperty
@property
@abc.abstractmethod
def action_features(self) -> dict:
pass
@abc.abstractproperty
@property
@abc.abstractmethod
def is_connected(self) -> bool:
pass
@@ -66,7 +69,8 @@ class Robot(abc.ABC):
"""Connects to the robot."""
pass
@abc.abstractproperty
@property
@abc.abstractmethod
def is_calibrated(self) -> bool:
pass

View File

@@ -61,7 +61,7 @@ conda install ffmpeg -c conda-forge
Install 🤗 LeRobot:
```bash
cd lerobot && pip install ".[feetech]"
cd lerobot && pip install -e ".[feetech]"
```
> [!NOTE]

View File

@@ -20,30 +20,6 @@ from lerobot.common.robots import RobotConfig
from .robot import Robot
def make_robot_config(robot_type: str, **kwargs) -> RobotConfig:
if robot_type == "aloha":
raise NotImplementedError # TODO
elif robot_type == "koch_follower":
from .koch_follower.config_koch_follower import KochFollowerConfig
return KochFollowerConfig(**kwargs)
elif robot_type == "so100_follower":
from .so100_follower.config_so100_follower import SO100FollowerConfig
return SO100FollowerConfig(**kwargs)
elif robot_type == "stretch":
from .stretch3.configuration_stretch3 import Stretch3RobotConfig
return Stretch3RobotConfig(**kwargs)
elif robot_type == "lekiwi":
from .lekiwi.config_lekiwi import LeKiwiConfig
return LeKiwiConfig(**kwargs)
else:
raise ValueError(f"Robot type '{robot_type}' is not available.")
def make_robot_from_config(config: RobotConfig) -> Robot:
if config.type == "koch_follower":
from .koch_follower import KochFollower

View File

@@ -47,15 +47,18 @@ class Teleoperator(abc.ABC):
def __str__(self) -> str:
return f"{self.id} {self.__class__.__name__}"
@abc.abstractproperty
@property
@abc.abstractmethod
def action_features(self) -> dict:
pass
@abc.abstractproperty
@property
@abc.abstractmethod
def feedback_features(self) -> dict:
pass
@abc.abstractproperty
@property
@abc.abstractmethod
def is_connected(self) -> bool:
pass
@@ -64,7 +67,8 @@ class Teleoperator(abc.ABC):
"""Connects to the teleoperator."""
pass
@abc.abstractproperty
@property
@abc.abstractmethod
def is_calibrated(self) -> bool:
pass

View File

@@ -78,15 +78,18 @@ class PreTrainedConfig(draccus.ChoiceRegistry, HubMixin, abc.ABC):
def type(self) -> str:
return self.get_choice_name(self.__class__)
@abc.abstractproperty
@property
@abc.abstractmethod
def observation_delta_indices(self) -> list | None:
raise NotImplementedError
@abc.abstractproperty
@property
@abc.abstractmethod
def action_delta_indices(self) -> list | None:
raise NotImplementedError
@abc.abstractproperty
@property
@abc.abstractmethod
def reward_delta_indices(self) -> list | None:
raise NotImplementedError

View File

@@ -125,7 +125,7 @@ def test_read(data_name, id_, value, dummy_motors):
)
mock__decode_sign.assert_called_once_with(data_name, {id_: value})
if data_name in bus.normalized_data:
mock__normalize.assert_called_once_with(data_name, {id_: value})
mock__normalize.assert_called_once_with({id_: value})
@pytest.mark.parametrize(
@@ -159,7 +159,7 @@ def test_write(data_name, id_, value, dummy_motors):
)
mock__encode_sign.assert_called_once_with(data_name, {id_: value})
if data_name in bus.normalized_data:
mock__unnormalize.assert_called_once_with(data_name, {id_: value})
mock__unnormalize.assert_called_once_with({id_: value})
@pytest.mark.parametrize(
@@ -196,7 +196,7 @@ def test_sync_read_by_str(data_name, id_, value, dummy_motors):
)
mock__decode_sign.assert_called_once_with(data_name, {id_: value})
if data_name in bus.normalized_data:
mock__normalize.assert_called_once_with(data_name, {id_: value})
mock__normalize.assert_called_once_with({id_: value})
@pytest.mark.parametrize(
@@ -233,7 +233,7 @@ def test_sync_read_by_list(data_name, ids_values, dummy_motors):
)
mock__decode_sign.assert_called_once_with(data_name, ids_values)
if data_name in bus.normalized_data:
mock__normalize.assert_called_once_with(data_name, ids_values)
mock__normalize.assert_called_once_with(ids_values)
@pytest.mark.parametrize(
@@ -270,7 +270,7 @@ def test_sync_read_by_none(data_name, ids_values, dummy_motors):
)
mock__decode_sign.assert_called_once_with(data_name, ids_values)
if data_name in bus.normalized_data:
mock__normalize.assert_called_once_with(data_name, ids_values)
mock__normalize.assert_called_once_with(ids_values)
@pytest.mark.parametrize(
@@ -304,7 +304,7 @@ def test_sync_write_by_single_value(data_name, value, dummy_motors):
)
mock__encode_sign.assert_called_once_with(data_name, ids_values)
if data_name in bus.normalized_data:
mock__unnormalize.assert_called_once_with(data_name, ids_values)
mock__unnormalize.assert_called_once_with(ids_values)
@pytest.mark.parametrize(
@@ -339,4 +339,4 @@ def test_sync_write_by_value_dict(data_name, ids_values, dummy_motors):
)
mock__encode_sign.assert_called_once_with(data_name, ids_values)
if data_name in bus.normalized_data:
mock__unnormalize.assert_called_once_with(data_name, ids_values)
mock__unnormalize.assert_called_once_with(ids_values)