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Author SHA1 Message Date
Martino Russi 6c9d8e9de1 Add custom teleop 2025-11-04 14:58:43 +01:00
4 changed files with 332 additions and 0 deletions
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#!/usr/bin/env python
# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# 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.
from .config_custom import CustomConfig
from .custom import Custom
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#!/usr/bin/env python
# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# 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.
from dataclasses import dataclass
from ..config import TeleoperatorConfig
@TeleoperatorConfig.register_subclass("custom")
@dataclass
class CustomConfig(TeleoperatorConfig):
"""Custom teleoperator config that dynamically wraps a base teleoperator class.
The base class and its configuration are loaded from a JSON config file at runtime.
Port and baud_rate are taken from the first device in the config file.
"""
config_path: str | None = None # REQUIRED: Path to custom config JSON file
port: str = "/dev/ttyACM0" # Default port
baud_rate: int = 115200 # Default baud rate
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#!/usr/bin/env python
# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# 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.
import importlib
import json
import logging
from pathlib import Path
from lerobot.motors.motors_bus import MotorNormMode
from ..teleoperator import Teleoperator
from .config_custom import CustomConfig
logger = logging.getLogger(__name__)
class Custom(Teleoperator):
"""
Custom teleoperator that dynamically wraps a base teleoperator class and applies configurable joint mapping.
The base class is specified in custom_config.json, allowing flexible teleoperator configurations.
"""
config_class = CustomConfig
name = "custom"
def __init__(self, config: CustomConfig):
# Load custom configuration from JSON file
if config.config_path is None:
raise ValueError(
"config_path must be provided for custom teleoperator. "
"Example: --teleop.config_path=/path/to/custom_config.json"
)
config_path = Path(config.config_path)
with open(config_path) as f:
custom_config = json.load(f)
logger.info(f"Loaded custom config from {config_path}")
logger.info(f"Found {len(custom_config)} teleoperator(s): {list(custom_config.keys())}")
# Initialize the base Teleoperator class
super().__init__(config)
# Store multiple base teleoperators and their action mappings
self.base_teleops = {}
self.robot_actions_configs = {}
# Instantiate each base teleoperator from the config
for device_name, device_config in custom_config.items():
base_class_name = device_config["base_class"]
# Create a config copy for this teleoperator
from dataclasses import replace
teleop_config = replace(
config,
port=device_config.get("port", config.port),
id=device_config.get("id", f"{config.id}_{device_name}"),
baud_rate=device_config.get("baud_rate", config.baud_rate)
)
logger.info(f" {device_name}: class={base_class_name}, port={teleop_config.port}, id={teleop_config.id}")
# Dynamically import and instantiate the base teleoperator class
module_path, class_name_full = base_class_name.rsplit(".", 1)
module = importlib.import_module(module_path)
base_class = getattr(module, class_name_full)
# Store the teleoperator and its action mapping
self.base_teleops[device_name] = base_class(teleop_config)
self.robot_actions_configs[device_name] = device_config["robot_actions"]
@property
def action_features(self) -> dict:
# Aggregate action features from all teleoperators' action mappings
all_actions = {}
for device_config in self.robot_actions_configs.values():
for robot_action in device_config.keys():
all_actions[robot_action] = float
return all_actions
@property
def feedback_features(self) -> dict:
# Aggregate feedback features from all base teleoperators
all_feedback = {}
for teleop in self.base_teleops.values():
all_feedback.update(teleop.feedback_features)
return all_feedback
@property
def is_connected(self) -> bool:
# All teleoperators must be connected
return all(teleop.is_connected for teleop in self.base_teleops.values())
@property
def is_calibrated(self) -> bool:
# All teleoperators must be calibrated
return all(teleop.is_calibrated for teleop in self.base_teleops.values())
def connect(self, calibrate: bool = True) -> None:
# Connect all base teleoperators
for device_name, teleop in self.base_teleops.items():
logger.info(f"Connecting {device_name}...")
teleop.connect(calibrate=calibrate)
def calibrate(self) -> None:
# Calibrate all base teleoperators
for device_name, teleop in self.base_teleops.items():
logger.info(f"Calibrating {device_name}...")
teleop.calibrate()
def configure(self) -> None:
# Configure all base teleoperators
for teleop in self.base_teleops.values():
teleop.configure()
def send_feedback(self, feedback: dict[str, float]) -> None:
# Send feedback to all base teleoperators
for teleop in self.base_teleops.values():
teleop.send_feedback(feedback)
def disconnect(self) -> None:
# Disconnect all base teleoperators
for device_name, teleop in self.base_teleops.items():
logger.info(f"Disconnecting {device_name}...")
teleop.disconnect()
def _normalize_to_unit_range(self, teleop, joint_name: str, value: float) -> float:
"""Convert a joint value from base teleoperator's normalization mode to [0, 1] range.
Args:
teleop: The base teleoperator instance
joint_name: Name of the joint (e.g., "shoulder_pitch")
value: Value in the base teleoperator's normalization mode
Returns:
Value normalized to [0, 1] range
"""
norm_mode = teleop.joints[joint_name]
if norm_mode == MotorNormMode.RANGE_M100_100:
# Convert from [-100, 100] to [0, 1]
return (value + 100.0) / 200.0
elif norm_mode == MotorNormMode.RANGE_0_100:
# Convert from [0, 100] to [0, 1]
return value / 100.0
elif norm_mode == MotorNormMode.DEGREES:
# For degrees, we need calibration to know the range
# Use calibration min/max to normalize
if teleop.calibration and joint_name in teleop.calibration:
min_deg = teleop.calibration[joint_name].range_min
max_deg = teleop.calibration[joint_name].range_max
if max_deg != min_deg:
return (value - min_deg) / (max_deg - min_deg)
# Fallback: assume common range like [-180, 180]
return (value + 180.0) / 360.0
else:
raise ValueError(f"Unknown normalization mode: {norm_mode}")
def get_action(self) -> dict[str, float]:
# Build action dict by reading from all base teleoperators
action = {}
# Loop through each teleoperator
for device_name, teleop in self.base_teleops.items():
# Read joint positions from this teleoperator
# These are in the teleoperator's normalization mode (e.g., -100 to 100)
joint_positions = teleop._read()
# Get the robot actions config for this teleoperator
robot_actions_config = self.robot_actions_configs[device_name]
# Process each robot action for this teleoperator
for robot_action, config in robot_actions_config.items():
if config["source"] == "neutral":
# Use fixed neutral value (already in [0, 1] range)
value = config["value"]
elif config["source"] == "teleop":
# Get value from teleop joint
teleop_joint = config["joint"]
value = joint_positions[teleop_joint]
# Convert from base teleoperator's normalization mode to [0, 1] range
value = self._normalize_to_unit_range(teleop, teleop_joint, value)
# Apply inversion if specified
if config.get("invert", False):
value = 1.0 - value
else:
raise ValueError(f"Unknown source '{config['source']}' for robot action '{robot_action}'")
action[robot_action] = value
return action
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{
"right_arm": {
"base_class": "lerobot.teleoperators.homunculus.homunculus_arm.HomunculusArm",
"port": "/dev/ttyACM0",
"id": "unitree_right",
"baud_rate": 115200,
"robot_actions": {
"kRightShoulderPitch.pos": {
"source": "neutral",
"value": 0.5
},
"kRightShoulderRoll.pos": {
"source": "neutral",
"value": 0.5
},
"kRightShoulderYaw.pos": {
"source": "neutral",
"value": 0.5
},
"kRightElbow.pos": {
"source": "neutral",
"value": 0.5
},
"kRightWristRoll.pos": {
"source": "teleop",
"joint": "wrist_roll",
"invert": true
},
"kRightWristPitch.pos": {
"source": "neutral",
"value": 0.5
},
"kRightWristYaw.pos": {
"source": "neutral",
"value": 0.5
}
}
},
"left_arm": {
"base_class": "lerobot.teleoperators.homunculus.homunculus_arm.HomunculusArm",
"port": "/dev/ttyACM1",
"id": "unitree_left",
"baud_rate": 115200,
"robot_actions": {
"kLeftShoulderPitch.pos": {
"source": "neutral",
"value": 0.5
},
"kLeftShoulderRoll.pos": {
"source": "neutral",
"value": 0.5
},
"kLeftShoulderYaw.pos": {
"source": "neutral",
"value": 0.5
},
"kLeftElbow.pos": {
"source": "neutral",
"value": 0.5
},
"kLeftWristRoll.pos": {
"source": "teleop",
"joint": "wrist_roll",
"invert": true
},
"kLeftWristPitch.pos": {
"source": "neutral",
"value": 0.5
},
"kLeftWristyaw.pos": {
"source": "neutral",
"value": 0.5
}
}
}
}