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https://github.com/huggingface/lerobot.git
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| 6c9d8e9de1 |
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#!/usr/bin/env python
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# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from .config_custom import CustomConfig
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from .custom import Custom
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#!/usr/bin/env python
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# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from dataclasses import dataclass
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from ..config import TeleoperatorConfig
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@TeleoperatorConfig.register_subclass("custom")
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@dataclass
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class CustomConfig(TeleoperatorConfig):
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"""Custom teleoperator config that dynamically wraps a base teleoperator class.
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The base class and its configuration are loaded from a JSON config file at runtime.
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Port and baud_rate are taken from the first device in the config file.
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"""
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config_path: str | None = None # REQUIRED: Path to custom config JSON file
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port: str = "/dev/ttyACM0" # Default port
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baud_rate: int = 115200 # Default baud rate
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#!/usr/bin/env python
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# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import importlib
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import json
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import logging
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from pathlib import Path
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from lerobot.motors.motors_bus import MotorNormMode
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from ..teleoperator import Teleoperator
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from .config_custom import CustomConfig
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logger = logging.getLogger(__name__)
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class Custom(Teleoperator):
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"""
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Custom teleoperator that dynamically wraps a base teleoperator class and applies configurable joint mapping.
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The base class is specified in custom_config.json, allowing flexible teleoperator configurations.
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"""
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config_class = CustomConfig
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name = "custom"
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def __init__(self, config: CustomConfig):
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# Load custom configuration from JSON file
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if config.config_path is None:
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raise ValueError(
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"config_path must be provided for custom teleoperator. "
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"Example: --teleop.config_path=/path/to/custom_config.json"
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)
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config_path = Path(config.config_path)
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with open(config_path) as f:
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custom_config = json.load(f)
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logger.info(f"Loaded custom config from {config_path}")
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logger.info(f"Found {len(custom_config)} teleoperator(s): {list(custom_config.keys())}")
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# Initialize the base Teleoperator class
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super().__init__(config)
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# Store multiple base teleoperators and their action mappings
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self.base_teleops = {}
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self.robot_actions_configs = {}
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# Instantiate each base teleoperator from the config
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for device_name, device_config in custom_config.items():
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base_class_name = device_config["base_class"]
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# Create a config copy for this teleoperator
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from dataclasses import replace
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teleop_config = replace(
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config,
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port=device_config.get("port", config.port),
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id=device_config.get("id", f"{config.id}_{device_name}"),
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baud_rate=device_config.get("baud_rate", config.baud_rate)
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)
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logger.info(f" {device_name}: class={base_class_name}, port={teleop_config.port}, id={teleop_config.id}")
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# Dynamically import and instantiate the base teleoperator class
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module_path, class_name_full = base_class_name.rsplit(".", 1)
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module = importlib.import_module(module_path)
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base_class = getattr(module, class_name_full)
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# Store the teleoperator and its action mapping
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self.base_teleops[device_name] = base_class(teleop_config)
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self.robot_actions_configs[device_name] = device_config["robot_actions"]
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@property
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def action_features(self) -> dict:
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# Aggregate action features from all teleoperators' action mappings
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all_actions = {}
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for device_config in self.robot_actions_configs.values():
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for robot_action in device_config.keys():
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all_actions[robot_action] = float
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return all_actions
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@property
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def feedback_features(self) -> dict:
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# Aggregate feedback features from all base teleoperators
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all_feedback = {}
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for teleop in self.base_teleops.values():
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all_feedback.update(teleop.feedback_features)
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return all_feedback
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@property
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def is_connected(self) -> bool:
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# All teleoperators must be connected
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return all(teleop.is_connected for teleop in self.base_teleops.values())
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@property
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def is_calibrated(self) -> bool:
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# All teleoperators must be calibrated
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return all(teleop.is_calibrated for teleop in self.base_teleops.values())
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def connect(self, calibrate: bool = True) -> None:
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# Connect all base teleoperators
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for device_name, teleop in self.base_teleops.items():
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logger.info(f"Connecting {device_name}...")
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teleop.connect(calibrate=calibrate)
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def calibrate(self) -> None:
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# Calibrate all base teleoperators
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for device_name, teleop in self.base_teleops.items():
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logger.info(f"Calibrating {device_name}...")
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teleop.calibrate()
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def configure(self) -> None:
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# Configure all base teleoperators
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for teleop in self.base_teleops.values():
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teleop.configure()
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def send_feedback(self, feedback: dict[str, float]) -> None:
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# Send feedback to all base teleoperators
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for teleop in self.base_teleops.values():
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teleop.send_feedback(feedback)
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def disconnect(self) -> None:
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# Disconnect all base teleoperators
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for device_name, teleop in self.base_teleops.items():
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logger.info(f"Disconnecting {device_name}...")
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teleop.disconnect()
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def _normalize_to_unit_range(self, teleop, joint_name: str, value: float) -> float:
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"""Convert a joint value from base teleoperator's normalization mode to [0, 1] range.
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Args:
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teleop: The base teleoperator instance
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joint_name: Name of the joint (e.g., "shoulder_pitch")
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value: Value in the base teleoperator's normalization mode
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Returns:
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Value normalized to [0, 1] range
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"""
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norm_mode = teleop.joints[joint_name]
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if norm_mode == MotorNormMode.RANGE_M100_100:
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# Convert from [-100, 100] to [0, 1]
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return (value + 100.0) / 200.0
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elif norm_mode == MotorNormMode.RANGE_0_100:
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# Convert from [0, 100] to [0, 1]
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return value / 100.0
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elif norm_mode == MotorNormMode.DEGREES:
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# For degrees, we need calibration to know the range
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# Use calibration min/max to normalize
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if teleop.calibration and joint_name in teleop.calibration:
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min_deg = teleop.calibration[joint_name].range_min
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max_deg = teleop.calibration[joint_name].range_max
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if max_deg != min_deg:
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return (value - min_deg) / (max_deg - min_deg)
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# Fallback: assume common range like [-180, 180]
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return (value + 180.0) / 360.0
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else:
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raise ValueError(f"Unknown normalization mode: {norm_mode}")
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def get_action(self) -> dict[str, float]:
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# Build action dict by reading from all base teleoperators
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action = {}
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# Loop through each teleoperator
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for device_name, teleop in self.base_teleops.items():
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# Read joint positions from this teleoperator
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# These are in the teleoperator's normalization mode (e.g., -100 to 100)
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joint_positions = teleop._read()
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# Get the robot actions config for this teleoperator
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robot_actions_config = self.robot_actions_configs[device_name]
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# Process each robot action for this teleoperator
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for robot_action, config in robot_actions_config.items():
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if config["source"] == "neutral":
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# Use fixed neutral value (already in [0, 1] range)
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value = config["value"]
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elif config["source"] == "teleop":
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# Get value from teleop joint
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teleop_joint = config["joint"]
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value = joint_positions[teleop_joint]
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# Convert from base teleoperator's normalization mode to [0, 1] range
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value = self._normalize_to_unit_range(teleop, teleop_joint, value)
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# Apply inversion if specified
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if config.get("invert", False):
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value = 1.0 - value
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else:
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raise ValueError(f"Unknown source '{config['source']}' for robot action '{robot_action}'")
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action[robot_action] = value
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return action
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@@ -0,0 +1,76 @@
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{
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"right_arm": {
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"base_class": "lerobot.teleoperators.homunculus.homunculus_arm.HomunculusArm",
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"port": "/dev/ttyACM0",
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"id": "unitree_right",
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"baud_rate": 115200,
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"robot_actions": {
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"kRightShoulderPitch.pos": {
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"source": "neutral",
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"value": 0.5
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},
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"kRightShoulderRoll.pos": {
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"source": "neutral",
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"value": 0.5
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},
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"kRightShoulderYaw.pos": {
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"source": "neutral",
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"value": 0.5
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},
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"kRightElbow.pos": {
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"source": "neutral",
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"value": 0.5
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},
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"kRightWristRoll.pos": {
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"source": "teleop",
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"joint": "wrist_roll",
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"invert": true
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},
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"kRightWristPitch.pos": {
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"source": "neutral",
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"value": 0.5
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},
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"kRightWristYaw.pos": {
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"source": "neutral",
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"value": 0.5
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}
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}
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},
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"left_arm": {
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"base_class": "lerobot.teleoperators.homunculus.homunculus_arm.HomunculusArm",
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"port": "/dev/ttyACM1",
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"id": "unitree_left",
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"baud_rate": 115200,
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"robot_actions": {
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"kLeftShoulderPitch.pos": {
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"source": "neutral",
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"value": 0.5
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},
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"kLeftShoulderRoll.pos": {
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"source": "neutral",
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"value": 0.5
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},
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"kLeftShoulderYaw.pos": {
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"source": "neutral",
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"value": 0.5
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},
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"kLeftElbow.pos": {
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"source": "neutral",
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"value": 0.5
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},
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"kLeftWristRoll.pos": {
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"source": "teleop",
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"joint": "wrist_roll",
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"invert": true
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},
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"kLeftWristPitch.pos": {
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"source": "neutral",
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"value": 0.5
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},
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"kLeftWristyaw.pos": {
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"source": "neutral",
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"value": 0.5
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}
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}
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}
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}
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Reference in New Issue
Block a user