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POC adding a leader/follower hack for Reachy
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Steve Nguyen committed Nov 27, 2024
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342 changes: 342 additions & 0 deletions lerobot/common/robot_devices/robots/reachy2_manipulator.py
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#!/usr/bin/env python

# Copyright 2024 The Pollen Robotics team and 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 json
import time
from copy import copy
from dataclasses import dataclass, field, replace

import numpy as np
import torch
from lerobot.common.robot_devices.cameras.reachy2 import ReachyCamera
from lerobot.common.robot_devices.motors.feetech import FeetechMotorsBus
from reachy2_sdk import ReachySDK

REACHY_MOTORS = [
"neck_yaw.pos",
"neck_pitch.pos",
"neck_roll.pos",
"r_shoulder_pitch.pos",
"r_shoulder_roll.pos",
"r_elbow_yaw.pos",
"r_elbow_pitch.pos",
"r_wrist_roll.pos",
"r_wrist_pitch.pos",
"r_wrist_yaw.pos",
"r_gripper.pos",
"l_shoulder_pitch.pos",
"l_shoulder_roll.pos",
"l_elbow_yaw.pos",
"l_elbow_pitch.pos",
"l_wrist_roll.pos",
"l_wrist_pitch.pos",
"l_wrist_yaw.pos",
"l_gripper.pos",
"mobile_base.vx",
"mobile_base.vy",
"mobile_base.vtheta",
]


@dataclass
class ReachyManipulatorRobotConfig:
robot_type: str | None = "reachy2"
cameras: dict[str, ReachyCamera] = field(default_factory=lambda: {})
ip_address: str | None = "172.17.135.207"
# ip_address: str | None = "192.168.0.197"
# ip_address: str | None = "localhost"


class ReachyManipulatorRobot:
"""Wrapper of ReachySDK"""

def __init__(self, config: ReachyRobotManipulatorConfig | None = None, **kwargs):
if config is None:
config = ReachyRobotManipulatorConfig()

# Overwrite config arguments using kwargs
self.config = replace(config, **kwargs)

self.robot_type = self.config.robot_type
self.cameras = self.config.cameras
self.has_camera = True
self.num_cameras = len(self.cameras)
self.is_connected = False
self.teleop = None
self.logs = {}
self.reachy = None
self.mobile_base_available = False

self.state_keys = None
self.action_keys = None

self.leader_arm = FeetechMotorsBus(config.leader_arm.port, config.leader_arm.motors)
self.leader_calib_dir=config.leader_arm.calibration_dir

@property
def camera_features(self) -> dict:
cam_ft = {}
for cam_key, cam in self.cameras.items():
key = f"observation.images.{cam_key}"
cam_ft[key] = {
"shape": (cam.height, cam.width, cam.channels),
"names": ["height", "width", "channels"],
"info": None,
}
return cam_ft

@property
def motor_features(self) -> dict:
motors = REACHY_MOTORS
# if self.mobile_base_available:
# motors += REACHY_MOBILE_BASE
return {
"action": {
"dtype": "float32",
"shape": (len(motors),),
"names": motors,
},
"observation.state": {
"dtype": "float32",
"shape": (len(motors),),
"names": motors,
},
}

@property
def features(self):
return {**self.motor_features, **self.camera_features}

def connect(self) -> None:
self.reachy = ReachySDK(host=self.config.ip_address)
print("Connecting to Reachy")
self.reachy.connect()
self.is_connected = self.reachy.is_connected
if not self.is_connected:
print(
f"Cannot connect to Reachy at address {self.config.ip_address}. Maybe a connection already exists."
)
raise ConnectionError()
# self.reachy.turn_on()
print(self.cameras)
if self.cameras is not None:
for name in self.cameras:
print(f"Connecting camera: {name}")
self.cameras[name].connect()
self.is_connected = self.is_connected and self.cameras[name].is_connected

if not self.is_connected:
print("Could not connect to the cameras, check that all cameras are plugged-in.")
raise ConnectionError()

self.mobile_base_available = self.reachy.mobile_base is not None

print("Connecting to leader arm")
self.leader_arm.connect()

with open(self.leader_arm.calibration_dir) as f:
self.leader_arm.calibration = json.load(f)
self.leader_arm.set_calibration(self.leader_arm.calibration)
self.leader_arm.apply_calibration()

def run_calibration(self):
pass

def teleop_step(
self, record_data=False
) -> None | tuple[dict[str, torch.Tensor], dict[str, torch.Tensor]]:
if not record_data:
return


#get leader arm
leader_pos = {}
for name in self.leader_arm:
before_lread_t = time.perf_counter()
leader_pos[name] = self.leader_arm[name].read("Present_Position")
leader_pos[name] = torch.from_numpy(leader_pos[name])
self.logs[f"read_leader_{name}_pos_dt_s"] = time.perf_counter() - before_lread_t


#TODO leader arm FK
#TODO senf task space poses
action = {}
action["neck_roll.pos"] = self.reachy.head.neck.roll.goal_position
action["neck_pitch.pos"] = self.reachy.head.neck.pitch.goal_position
action["neck_yaw.pos"] = self.reachy.head.neck.yaw.goal_position

action["r_shoulder_pitch.pos"] = self.reachy.r_arm.shoulder.pitch.goal_position
action["r_shoulder_roll.pos"] = self.reachy.r_arm.shoulder.roll.goal_position
action["r_elbow_yaw.pos"] = self.reachy.r_arm.elbow.yaw.goal_position
action["r_elbow_pitch.pos"] = self.reachy.r_arm.elbow.pitch.goal_position
action["r_wrist_roll.pos"] = self.reachy.r_arm.wrist.roll.goal_position
action["r_wrist_pitch.pos"] = self.reachy.r_arm.wrist.pitch.goal_position
action["r_wrist_yaw.pos"] = self.reachy.r_arm.wrist.yaw.goal_position
action["r_gripper.pos"] = self.reachy.r_arm.gripper.opening

action["l_shoulder_pitch.pos"] = self.reachy.l_arm.shoulder.pitch.goal_position
action["l_shoulder_roll.pos"] = self.reachy.l_arm.shoulder.roll.goal_position
action["l_elbow_yaw.pos"] = self.reachy.l_arm.elbow.yaw.goal_position
action["l_elbow_pitch.pos"] = self.reachy.l_arm.elbow.pitch.goal_position
action["l_wrist_roll.pos"] = self.reachy.l_arm.wrist.roll.goal_position
action["l_wrist_pitch.pos"] = self.reachy.l_arm.wrist.pitch.goal_position
action["l_wrist_yaw.pos"] = self.reachy.l_arm.wrist.yaw.goal_position
action["l_gripper.pos"] = self.reachy.l_arm.gripper.opening

if self.mobile_base_available:
last_cmd_vel = self.reachy.mobile_base.last_cmd_vel
action["mobile_base_x.vel"] = last_cmd_vel["x"]
action["mobile_base_y.vel"] = last_cmd_vel["y"]
action["mobile_base_theta.vel"] = last_cmd_vel["theta"]
else:
action["mobile_base_x.vel"] = 0
action["mobile_base_y.vel"] = 0
action["mobile_base_theta.vel"] = 0

dtype = self.motor_features["action"]["dtype"]
action = np.array(list(action.values()), dtype=dtype)
# action = torch.as_tensor(list(action.values()))

obs_dict = self.capture_observation()
action_dict = {}
action_dict["action"] = action

return obs_dict, action_dict

def get_state(self) -> dict:
# neck roll, pitch, yaw
# r_shoulder_pitch, r_shoulder_roll, r_elbow_yaw, r_elbow_pitch, r_wrist_roll, r_wrist_pitch, r_wrist_yaw, r_gripper
# l_shoulder_pitch, l_shoulder_roll, l_elbow_yaw, l_elbow_pitch, l_wrist_roll, l_wrist_pitch, l_wrist_yaw, l_gripper
# mobile base x, y, theta
if self.is_connected:
if self.mobile_base_available:
odometry = self.reachy.mobile_base.odometry
else:
odometry = {"x": 0, "y": 0, "theta": 0, "vx": 0, "vy": 0, "vtheta": 0}
return {
"neck_yaw.pos": self.reachy.head.neck.yaw.present_position,
"neck_pitch.pos": self.reachy.head.neck.pitch.present_position,
"neck_roll.pos": self.reachy.head.neck.roll.present_position,
"r_shoulder_pitch.pos": self.reachy.r_arm.shoulder.pitch.present_position,
"r_shoulder_roll.pos": self.reachy.r_arm.shoulder.roll.present_position,
"r_elbow_yaw.pos": self.reachy.r_arm.elbow.yaw.present_position,
"r_elbow_pitch.pos": self.reachy.r_arm.elbow.pitch.present_position,
"r_wrist_roll.pos": self.reachy.r_arm.wrist.roll.present_position,
"r_wrist_pitch.pos": self.reachy.r_arm.wrist.pitch.present_position,
"r_wrist_yaw.pos": self.reachy.r_arm.wrist.yaw.present_position,
"r_gripper.pos": self.reachy.r_arm.gripper.present_position,
"l_shoulder_pitch.pos": self.reachy.l_arm.shoulder.pitch.present_position,
"l_shoulder_roll.pos": self.reachy.l_arm.shoulder.roll.present_position,
"l_elbow_yaw.pos": self.reachy.l_arm.elbow.yaw.present_position,
"l_elbow_pitch.pos": self.reachy.l_arm.elbow.pitch.present_position,
"l_wrist_roll.pos": self.reachy.l_arm.wrist.roll.present_position,
"l_wrist_pitch.pos": self.reachy.l_arm.wrist.pitch.present_position,
"l_wrist_yaw.pos": self.reachy.l_arm.wrist.yaw.present_position,
"l_gripper.pos": self.reachy.l_arm.gripper.present_position,
"mobile_base.vx": odometry["vx"],
"mobile_base.vy": odometry["vy"],
"mobile_base.vtheta": odometry["vtheta"],
}
else:
return {}

def capture_observation(self) -> dict:
if self.is_connected:
before_read_t = time.perf_counter()
state = self.get_state()
self.logs["read_pos_dt_s"] = time.perf_counter() - before_read_t

if self.state_keys is None:
self.state_keys = list(state)

dtype = self.motor_features["observation.state"]["dtype"]
state = np.array(list(state.values()), dtype=dtype)
# state = torch.as_tensor(list(state.values()))

# Capture images from cameras
images = {}
for name in self.cameras:
# before_camread_t = time.perf_counter()
images[name] = self.cameras[name].read() # Reachy cameras read() is not blocking?
# print(f'name: {name} img: {images[name]}')
if images[name] is not None:
# images[name] = copy(images[name][0]) # seems like I need to copy?
images[name] = torch.from_numpy(copy(images[name][0])) # seems like I need to copy?
self.logs[f"read_camera_{name}_dt_s"] = images[name][1] # full timestamp, TODO dt

# Populate output dictionnaries
obs_dict = {}
obs_dict["observation.state"] = state
for name in self.cameras:
obs_dict[f"observation.images.{name}"] = images[name]

return obs_dict
else:
return {}

def send_action(self, action: torch.Tensor) -> torch.Tensor:
if not self.is_connected:
raise ConnectionError()

self.reachy.head.neck.yaw.goal_position = float(action[0])
self.reachy.head.neck.pitch.goal_position = float(action[1])
self.reachy.head.neck.roll.goal_position = float(action[2])

self.reachy.r_arm.shoulder.pitch.goal_position = float(action[3])
self.reachy.r_arm.shoulder.roll.goal_position = float(action[4])
self.reachy.r_arm.elbow.yaw.goal_position = float(action[5])
self.reachy.r_arm.elbow.pitch.goal_position = float(action[6])
self.reachy.r_arm.wrist.roll.goal_position = float(action[7])
self.reachy.r_arm.wrist.roll.goal_position = float(action[8])
self.reachy.r_arm.wrist.yaw.goal_position = float(action[9])
self.reachy.r_arm.gripper.set_opening(float(action[10]))

self.reachy.l_arm.shoulder.pitch.goal_position = float(action[11])
self.reachy.l_arm.shoulder.roll.goal_position = float(action[12])
self.reachy.l_arm.elbow.yaw.goal_position = float(action[13])
self.reachy.l_arm.elbow.pitch.goal_position = float(action[14])
self.reachy.l_arm.wrist.roll.goal_position = float(action[15])
self.reachy.l_arm.wrist.roll.goal_position = float(action[16])
self.reachy.l_arm.wrist.yaw.goal_position = float(action[17])
self.reachy.l_arm.gripper.set_opening(float(action[18]))

s = time.time()
self.reachy.send_goal_positions(check_positions=False)
print("send_goal_positions", time.time() - s)

if self.mobile_base_available:
self.reachy.mobile_base.set_goal_speed(action[19], action[20], action[21])
self.reachy.mobile_base.send_speed_command()

# TODO: what shape is the action tensor?
# 7 dofs per arm (x2)
# 1 dof per gripper (x2)
# 3 dofs for the neck
# 3 dofs for the mobile base (x, y, theta)
# 7+7+1+1+3+3 = 22
return action

def print_logs(self) -> None:
pass

def disconnect(self) -> None:
print("Disconnecting")
self.is_connected = False
print("Turn off")
# self.reachy.turn_off_smoothly()
# self.reachy.turn_off()
print("\t turn off done")
self.reachy.disconnect()
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