239 lines
8.9 KiB
Python
239 lines
8.9 KiB
Python
"""Contains logic to instantiate a robot, read information from its motors and cameras,
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and send orders to its motors.
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"""
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# TODO(rcadene, aliberts): reorganize the codebase into one file per robot, with the associated
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# calibration procedure, to make it easy for people to add their own robot.
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import json
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import logging
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import time
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import numpy as np
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from lerobot.common.cameras.utils import make_cameras_from_configs
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from lerobot.common.constants import OBS_IMAGES, OBS_STATE
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from lerobot.common.errors import DeviceAlreadyConnectedError, DeviceNotConnectedError
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from lerobot.common.motors import TorqueMode
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from lerobot.common.motors.dynamixel import (
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DynamixelMotorsBus,
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run_arm_calibration,
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)
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from ..robot import Robot
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from ..utils import ensure_safe_goal_position
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from .configuration_viperx import ViperXRobotConfig
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class ViperXRobot(Robot):
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"""
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[ViperX](https://www.trossenrobotics.com/viperx-300) developed by Trossen Robotics
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"""
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config_class = ViperXRobotConfig
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name = "viperx"
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def __init__(
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self,
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config: ViperXRobotConfig,
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):
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super().__init__(config)
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self.config = config
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self.robot_type = config.type
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self.arm = DynamixelMotorsBus(
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port=self.config.port,
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motors={
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"waist": config.waist,
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"shoulder": config.shoulder,
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"shoulder_shadow": config.shoulder_shadow,
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"elbow": config.elbow,
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"elbow_shadow": config.elbow_shadow,
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"forearm_roll": config.forearm_roll,
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"wrist_angle": config.wrist_angle,
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"wrist_rotate": config.wrist_rotate,
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"gripper": config.gripper,
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},
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)
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self.cameras = make_cameras_from_configs(config.cameras)
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self.is_connected = False
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self.logs = {}
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@property
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def state_feature(self) -> dict:
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return {
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"dtype": "float32",
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"shape": (len(self.arm),),
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"names": {"motors": list(self.arm.motors)},
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}
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@property
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def action_feature(self) -> dict:
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return self.state_feature
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@property
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def camera_features(self) -> dict[str, dict]:
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cam_ft = {}
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for cam_key, cam in self.cameras.items():
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key = f"observation.images.{cam_key}"
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cam_ft[key] = {
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"shape": (cam.height, cam.width, cam.channels),
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"names": ["height", "width", "channels"],
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"info": None,
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}
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return cam_ft
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def _set_shadow_motors(self):
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"""
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Set secondary/shadow ID for shoulder and elbow. These joints have two motors.
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As a result, if only one of them is required to move to a certain position,
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the other will follow. This is to avoid breaking the motors.
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"""
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shoulder_idx = self.config.shoulder[0]
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self.arm.write("Secondary_ID", shoulder_idx, "shoulder_shadow")
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elbow_idx = self.config.elbow[0]
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self.arm.write("Secondary_ID", elbow_idx, "elbow_shadow")
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def connect(self):
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if self.is_connected:
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raise DeviceAlreadyConnectedError(
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"ManipulatorRobot is already connected. Do not run `robot.connect()` twice."
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)
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logging.info("Connecting arm.")
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self.arm.connect()
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# We assume that at connection time, arm is in a rest position,
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# and torque can be safely disabled to run calibration.
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self.arm.write("Torque_Enable", TorqueMode.DISABLED.value)
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self.calibrate()
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self._set_shadow_motors()
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# Set a velocity limit of 131 as advised by Trossen Robotics
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self.arm.write("Velocity_Limit", 131)
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# Use 'extended position mode' for all motors except gripper, because in joint mode the servos can't
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# rotate more than 360 degrees (from 0 to 4095) And some mistake can happen while assembling the arm,
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# you could end up with a servo with a position 0 or 4095 at a crucial point See [
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# https://emanual.robotis.com/docs/en/dxl/x/x_series/#operating-mode11]
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all_motors_except_gripper = [name for name in self.arm.motor_names if name != "gripper"]
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if len(all_motors_except_gripper) > 0:
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# 4 corresponds to Extended Position on Aloha motors
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self.arm.write("Operating_Mode", 4, all_motors_except_gripper)
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# Use 'position control current based' for follower gripper to be limited by the limit of the current.
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# It can grasp an object without forcing too much even tho,
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# it's goal position is a complete grasp (both gripper fingers are ordered to join and reach a touch).
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# 5 corresponds to Current Controlled Position on Aloha gripper follower "xm430-w350"
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self.arm.write("Operating_Mode", 5, "gripper")
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# Note: We can't enable torque on the leader gripper since "xc430-w150" doesn't have
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# a Current Controlled Position mode.
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logging.info("Activating torque.")
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self.arm.write("Torque_Enable", TorqueMode.ENABLED.value)
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# Check arm can be read
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self.arm.read("Present_Position")
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# Connect the cameras
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for cam in self.cameras.values():
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cam.connect()
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self.is_connected = True
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def calibrate(self):
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"""After calibration all motors function in human interpretable ranges.
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Rotations are expressed in degrees in nominal range of [-180, 180],
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and linear motions (like gripper of Aloha) in nominal range of [0, 100].
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"""
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if self.calibration_fpath.exists():
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with open(self.calibration_fpath) as f:
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calibration = json.load(f)
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else:
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# TODO(rcadene): display a warning in __init__ if calibration file not available
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logging.info(f"Missing calibration file '{self.calibration_fpath}'")
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calibration = run_arm_calibration(self.arm, self.robot_type, self.name, "follower")
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logging.info(f"Calibration is done! Saving calibration file '{self.calibration_fpath}'")
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self.calibration_fpath.parent.mkdir(parents=True, exist_ok=True)
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with open(self.calibration_fpath, "w") as f:
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json.dump(calibration, f)
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self.arm.set_calibration(calibration)
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def get_observation(self) -> dict[str, np.ndarray]:
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"""The returned observations do not have a batch dimension."""
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if not self.is_connected:
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raise DeviceNotConnectedError(
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"ManipulatorRobot is not connected. You need to run `robot.connect()`."
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)
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obs_dict = {}
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# Read arm position
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before_read_t = time.perf_counter()
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obs_dict[OBS_STATE] = self.arm.read("Present_Position")
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self.logs["read_pos_dt_s"] = time.perf_counter() - before_read_t
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# Capture images from cameras
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for cam_key, cam in self.cameras.items():
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before_camread_t = time.perf_counter()
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obs_dict[f"{OBS_IMAGES}.{cam_key}"] = cam.async_read()
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self.logs[f"read_camera_{cam_key}_dt_s"] = cam.logs["delta_timestamp_s"]
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self.logs[f"async_read_camera_{cam_key}_dt_s"] = time.perf_counter() - before_camread_t
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return obs_dict
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def send_action(self, action: np.ndarray) -> np.ndarray:
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"""Command arm to move to a target joint configuration.
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The relative action magnitude may be clipped depending on the configuration parameter
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`max_relative_target`. In this case, the action sent differs from original action.
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Thus, this function always returns the action actually sent.
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Args:
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action (np.ndarray): array containing the goal positions for the motors.
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Raises:
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RobotDeviceNotConnectedError: if robot is not connected.
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Returns:
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np.ndarray: the action sent to the motors, potentially clipped.
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"""
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if not self.is_connected:
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raise DeviceNotConnectedError(
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"ManipulatorRobot is not connected. You need to run `robot.connect()`."
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)
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goal_pos = action
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# Cap goal position when too far away from present position.
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# /!\ Slower fps expected due to reading from the follower.
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if self.config.max_relative_target is not None:
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present_pos = self.arm.read("Present_Position")
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goal_pos = ensure_safe_goal_position(goal_pos, present_pos, self.config.max_relative_target)
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# Send goal position to the arm
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self.arm.write("Goal_Position", goal_pos.astype(np.int32))
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return goal_pos
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def print_logs(self):
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# TODO(aliberts): move robot-specific logs logic here
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pass
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def disconnect(self):
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if not self.is_connected:
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raise DeviceNotConnectedError(
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"ManipulatorRobot is not connected. You need to run `robot.connect()` before disconnecting."
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)
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self.arm.disconnect()
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for cam in self.cameras.values():
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cam.disconnect()
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self.is_connected = False
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