From 496eb6298e6174fd56d82d59973a782c1c758adf Mon Sep 17 00:00:00 2001
From: DUDULRX <162013353+DUDULRX@users.noreply.github.com>
Date: Wed, 5 Mar 2025 20:00:42 +0800
Subject: [PATCH] Added a roarm_m3 for robotic arm adaptation, and modified the
keyboard listening method to adapt to the screenless mode
---
examples/12_use_roarm_m3.md | 140 ++++++++
lerobot/common/datasets/lerobot_dataset.py | 12 +-
lerobot/common/datasets/utils.py | 14 -
.../datasets/v2/convert_dataset_v1_to_v2.py | 3 +
.../v21/convert_dataset_v20_to_v21.py | 2 +-
lerobot/common/policies/pi0/modeling_pi0.py | 2 +-
.../common/robot_devices/cameras/opencv.py | 17 +
lerobot/common/robot_devices/cameras/utils.py | 2 +-
lerobot/common/robot_devices/control_utils.py | 92 ++++--
.../common/robot_devices/robots/configs.py | 40 ++-
.../robots/mobile_manipulator.py | 24 +-
.../common/robot_devices/robots/roarm_m3.py | 306 ++++++++++++++++++
lerobot/common/robot_devices/robots/utils.py | 8 +-
lerobot/common/utils/utils.py | 39 +--
lerobot/scripts/control_robot.py | 5 +-
lerobot/scripts/eval.py | 4 +-
lerobot/scripts/visualize_dataset_html.py | 19 +-
.../templates/visualize_dataset_template.html | 113 +++----
18 files changed, 671 insertions(+), 171 deletions(-)
create mode 100644 examples/12_use_roarm_m3.md
create mode 100644 lerobot/common/robot_devices/robots/roarm_m3.py
diff --git a/examples/12_use_roarm_m3.md b/examples/12_use_roarm_m3.md
new file mode 100644
index 00000000..eabeaf8a
--- /dev/null
+++ b/examples/12_use_roarm_m3.md
@@ -0,0 +1,140 @@
+# Using the [roarm_m3](https://github.com/waveshareteam/roarm_m3) with LeRobot
+
+## Table of Contents
+
+ - [A. Teleoperate](#a-teleoperate)
+ - [B. Record a dataset](#b-record-a-dataset)
+ - [C. Visualize a dataset](#c-visualize-a-dataset)
+ - [D. Replay an episode](#d-replay-an-episode)
+ - [E. Train a policy](#e-train-a-policy)
+ - [F. Evaluate your policy](#f-evaluate-your-policy)
+ - [G. More Information](#g-more-information)
+
+## A. Teleoperate
+
+**Simple teleop**
+#### a. Teleop without displaying cameras
+You will be able to teleoperate your robot! (it won't connect and display the cameras):
+```bash
+python lerobot/scripts/control_robot.py \
+ --robot.type=roarm_m3 \
+ --robot.cameras='{}' \
+ --control.type=teleoperate
+```
+
+
+#### b. Teleop with displaying cameras
+You will be able to display the cameras while you are teleoperating by running the following code. This is useful to prepare your setup before recording your first dataset.
+```bash
+python lerobot/scripts/control_robot.py \
+ --robot.type=roarm_m3 \
+ --control.type=teleoperate
+```
+
+## B. Record a dataset
+
+Once you're familiar with teleoperation, you can record your first dataset with roarm_m3.
+
+If you want to use the Hugging Face hub features for uploading your dataset and you haven't previously done it, make sure you've logged in using a write-access token, which can be generated from the [Hugging Face settings](https://huggingface.co/settings/tokens):
+```bash
+huggingface-cli login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
+```
+
+Store your Hugging Face repository name in a variable to run these commands:
+```bash
+HF_USER=$(huggingface-cli whoami | head -n 1)
+echo $HF_USER
+```
+
+Record 2 episodes and upload your dataset to the hub:
+```bash
+python lerobot/scripts/control_robot.py \
+ --robot.type=roarm_m3 \
+ --control.type=record \
+ --control.fps=30 \
+ --control.single_task="Grasp a block and put it in the bin." \
+ --control.repo_id=${HF_USER}/roarm_m3_test \
+ --control.tags='["roarm_m3","tutorial"]' \
+ --control.warmup_time_s=5 \
+ --control.episode_time_s=30 \
+ --control.reset_time_s=30 \
+ --control.num_episodes=2 \
+ --control.push_to_hub=true
+```
+
+Note: You can resume recording by adding `--control.resume=true`.
+
+## C. Visualize a dataset
+
+If you uploaded your dataset to the hub with `--control.push_to_hub=true`, you can [visualize your dataset online](https://huggingface.co/spaces/lerobot/visualize_dataset) by copy pasting your repo id given by:
+```bash
+echo ${HF_USER}/roarm_m3_test
+```
+
+If you didn't upload with `--control.push_to_hub=false`, you can also visualize it locally with (a window can be opened in the browser `http://ip:9090` with the visualization tool):
+```bash
+python lerobot/scripts/visualize_dataset_html.py \
+ --repo-id ${HF_USER}/roarm_m3_test \
+ --host ip \
+ --local-files-only 1
+```
+
+## D. Replay an episode
+
+Now try to replay episode nth on your bot:
+```bash
+python lerobot/scripts/control_robot.py \
+ --robot.type=roarm_m3 \
+ --control.type=replay \
+ --control.fps=30 \
+ --control.repo_id=${HF_USER}/roarm_m3_test \
+ --control.episode=n-1
+```
+
+## E. Train a policy
+
+To train a policy to control your robot, use the [`python lerobot/scripts/train.py`](../lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:
+```bash
+python lerobot/scripts/train.py \
+ --dataset.repo_id=${HF_USER}/roarm_m3_test \
+ --policy.type=act \
+ --output_dir=outputs/train/act_roarm_m3_test \
+ --job_name=act_roarm_m3_test \
+ --device=cuda \
+ --wandb.enable=true
+```
+
+Let's explain it:
+1. We provided the dataset as argument with `--dataset.repo_id=${HF_USER}/roarm_m3_test`.
+2. We provided the policy with `policy.type=act`. This loads configurations from [`configuration_act.py`](../lerobot/common/policies/act/configuration_act.py). Importantly, this policy will automatically adapt to the number of motor sates, motor actions and cameras of your robot (e.g. `laptop` and `phone`) which have been saved in your dataset.
+4. We provided `device=cuda` since we are training on a Nvidia GPU, but you could use `device=mps` to train on Apple silicon.
+5. We provided `wandb.enable=true` to use [Weights and Biases](https://docs.wandb.ai/quickstart) for visualizing training plots. This is optional but if you use it, make sure you are logged in by running `wandb login`.
+
+Training should take several hours. You will find checkpoints in `outputs/train/act_roarm_m3_test/checkpoints`.
+
+## F. Evaluate your policy
+
+You can use the `record` function from [`lerobot/scripts/control_robot.py`](../lerobot/scripts/control_robot.py) but with a policy checkpoint as input. For instance, run this command to record 10 evaluation episodes:
+```bash
+python lerobot/scripts/control_robot.py \
+ --robot.type=roarm_m3 \
+ --control.type=record \
+ --control.fps=30 \
+ --control.single_task="Grasp a block and put it in the bin." \
+ --control.repo_id=${HF_USER}/eval_act_roarm_m3_test \
+ --control.tags='["tutorial"]' \
+ --control.warmup_time_s=5 \
+ --control.episode_time_s=30 \
+ --control.reset_time_s=30 \
+ --control.num_episodes=10 \
+ --control.push_to_hub=true \
+ --control.policy.path=outputs/train/act_roarm_m3_test/checkpoints/last/pretrained_model
+```
+
+As you can see, it's almost the same command as previously used to record your training dataset. Two things changed:
+1. There is an additional `--control.policy.path` argument which indicates the path to your policy checkpoint with (e.g. `outputs/train/eval_act_roarm_m3_test/checkpoints/last/pretrained_model`). You can also use the model repository if you uploaded a model checkpoint to the hub (e.g. `${HF_USER}/act_roarm_m3_test`).
+2. The name of dataset begins by `eval` to reflect that you are running inference (e.g. `${HF_USER}/eval_act_roarm_m3_test`).
+
+## G. More Information
+
+Follow this [previous tutorial](https://github.com/huggingface/lerobot/blob/main/examples/7_get_started_with_real_robot.md#4-train-a-policy-on-your-data) for a more in-depth tutorial on controlling real robots with LeRobot.
diff --git a/lerobot/common/datasets/lerobot_dataset.py b/lerobot/common/datasets/lerobot_dataset.py
index 5414c76d..505c33b2 100644
--- a/lerobot/common/datasets/lerobot_dataset.py
+++ b/lerobot/common/datasets/lerobot_dataset.py
@@ -13,7 +13,6 @@
# 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 contextlib
import logging
import shutil
from pathlib import Path
@@ -28,7 +27,6 @@ import torch.utils
from datasets import concatenate_datasets, load_dataset
from huggingface_hub import HfApi, snapshot_download
from huggingface_hub.constants import REPOCARD_NAME
-from huggingface_hub.errors import RevisionNotFoundError
from lerobot.common.constants import HF_LEROBOT_HOME
from lerobot.common.datasets.compute_stats import aggregate_stats, compute_episode_stats
@@ -314,7 +312,7 @@ class LeRobotDatasetMetadata:
obj.repo_id = repo_id
obj.root = Path(root) if root is not None else HF_LEROBOT_HOME / repo_id
- obj.root.mkdir(parents=True, exist_ok=False)
+ obj.root.mkdir(parents=True, exist_ok=True)
if robot is not None:
features = get_features_from_robot(robot, use_videos)
@@ -480,7 +478,7 @@ class LeRobotDataset(torch.utils.data.Dataset):
self.image_writer = None
self.episode_buffer = None
- self.root.mkdir(exist_ok=True, parents=True)
+ self.root.mkdir(exist_ok=False, parents=True)
# Load metadata
self.meta = LeRobotDatasetMetadata(
@@ -519,7 +517,6 @@ class LeRobotDataset(torch.utils.data.Dataset):
branch: str | None = None,
tags: list | None = None,
license: str | None = "apache-2.0",
- tag_version: bool = True,
push_videos: bool = True,
private: bool = False,
allow_patterns: list[str] | str | None = None,
@@ -565,11 +562,6 @@ class LeRobotDataset(torch.utils.data.Dataset):
)
card.push_to_hub(repo_id=self.repo_id, repo_type="dataset", revision=branch)
- if tag_version:
- with contextlib.suppress(RevisionNotFoundError):
- hub_api.delete_tag(self.repo_id, tag=CODEBASE_VERSION, repo_type="dataset")
- hub_api.create_tag(self.repo_id, tag=CODEBASE_VERSION, revision=branch, repo_type="dataset")
-
def pull_from_repo(
self,
allow_patterns: list[str] | str | None = None,
diff --git a/lerobot/common/datasets/utils.py b/lerobot/common/datasets/utils.py
index 7e297b35..89adb163 100644
--- a/lerobot/common/datasets/utils.py
+++ b/lerobot/common/datasets/utils.py
@@ -31,7 +31,6 @@ import packaging.version
import torch
from datasets.table import embed_table_storage
from huggingface_hub import DatasetCard, DatasetCardData, HfApi
-from huggingface_hub.errors import RevisionNotFoundError
from PIL import Image as PILImage
from torchvision import transforms
@@ -326,19 +325,6 @@ def get_safe_version(repo_id: str, version: str | packaging.version.Version) ->
)
hub_versions = get_repo_versions(repo_id)
- if not hub_versions:
- raise RevisionNotFoundError(
- f"""Your dataset must be tagged with a codebase version.
- Assuming _version_ is the codebase_version value in the info.json, you can run this:
- ```python
- from huggingface_hub import HfApi
-
- hub_api = HfApi()
- hub_api.create_tag("{repo_id}", tag="_version_", repo_type="dataset")
- ```
- """
- )
-
if target_version in hub_versions:
return f"v{target_version}"
diff --git a/lerobot/common/datasets/v2/convert_dataset_v1_to_v2.py b/lerobot/common/datasets/v2/convert_dataset_v1_to_v2.py
index acf0282f..fe658ce4 100644
--- a/lerobot/common/datasets/v2/convert_dataset_v1_to_v2.py
+++ b/lerobot/common/datasets/v2/convert_dataset_v1_to_v2.py
@@ -166,6 +166,9 @@ def parse_robot_config(robot_cfg: RobotConfig) -> tuple[str, dict]:
for arm in robot_cfg.leader_arms
for motor in robot_cfg.leader_arms[arm].motors
]
+ elif robot_cfg.type == "roarm_m3":
+ state_names = ["roam_m3","roam_m3","roam_m3","roam_m3","roam_m3","roam_m3"]
+ action_names = ["roam_m3","roam_m3","roam_m3","roam_m3","roam_m3","roam_m3"]
# elif robot_cfg["robot_type"] == "stretch3": TODO
else:
raise NotImplementedError(
diff --git a/lerobot/common/datasets/v21/convert_dataset_v20_to_v21.py b/lerobot/common/datasets/v21/convert_dataset_v20_to_v21.py
index 163a6003..20bda75b 100644
--- a/lerobot/common/datasets/v21/convert_dataset_v20_to_v21.py
+++ b/lerobot/common/datasets/v21/convert_dataset_v20_to_v21.py
@@ -57,7 +57,7 @@ def convert_dataset(
dataset.meta.info["codebase_version"] = CODEBASE_VERSION
write_info(dataset.meta.info, dataset.root)
- dataset.push_to_hub(branch=branch, tag_version=False, allow_patterns="meta/")
+ dataset.push_to_hub(branch=branch, allow_patterns="meta/")
# delete old stats.json file
if (dataset.root / STATS_PATH).is_file:
diff --git a/lerobot/common/policies/pi0/modeling_pi0.py b/lerobot/common/policies/pi0/modeling_pi0.py
index bc53bf85..c8b12caf 100644
--- a/lerobot/common/policies/pi0/modeling_pi0.py
+++ b/lerobot/common/policies/pi0/modeling_pi0.py
@@ -313,7 +313,7 @@ class PI0Policy(PreTrainedPolicy):
state = self.prepare_state(batch)
lang_tokens, lang_masks = self.prepare_language(batch)
actions = self.prepare_action(batch)
- actions_is_pad = batch.get("actions_is_pad")
+ actions_is_pad = batch.get("actions_id_pad")
loss_dict = {}
losses = self.model.forward(images, img_masks, lang_tokens, lang_masks, state, actions, noise, time)
diff --git a/lerobot/common/robot_devices/cameras/opencv.py b/lerobot/common/robot_devices/cameras/opencv.py
index 93c791fa..506f6075 100644
--- a/lerobot/common/robot_devices/cameras/opencv.py
+++ b/lerobot/common/robot_devices/cameras/opencv.py
@@ -30,6 +30,20 @@ from lerobot.common.utils.utils import capture_timestamp_utc
# treat the same cameras as new devices. Thus we select a higher bound to search indices.
MAX_OPENCV_INDEX = 60
+undistort = True
+def undistort_image(image):
+ import cv2
+ camera_matrix = np.array([
+ [289.11451, 0., 347.23664],
+ [0., 289.75319, 235.67429],
+ [0., 0., 1.]
+ ])
+
+ dist_coeffs = np.array([-0.208848, 0.028006, -0.000705, -0.000820, 0.000000])
+
+ undistorted_image = cv2.undistort(image, camera_matrix, dist_coeffs)
+
+ return undistorted_image
def find_cameras(raise_when_empty=False, max_index_search_range=MAX_OPENCV_INDEX, mock=False) -> list[dict]:
cameras = []
@@ -368,6 +382,9 @@ class OpenCVCamera:
color_image = cv2.cvtColor(color_image, cv2.COLOR_BGR2RGB)
+ if undistort:
+ color_image = undistort_image(color_image)
+
h, w, _ = color_image.shape
if h != self.height or w != self.width:
raise OSError(
diff --git a/lerobot/common/robot_devices/cameras/utils.py b/lerobot/common/robot_devices/cameras/utils.py
index ef6d8266..88288ea3 100644
--- a/lerobot/common/robot_devices/cameras/utils.py
+++ b/lerobot/common/robot_devices/cameras/utils.py
@@ -31,7 +31,7 @@ def make_cameras_from_configs(camera_configs: dict[str, CameraConfig]) -> list[C
cameras[key] = IntelRealSenseCamera(cfg)
else:
- raise ValueError(f"The camera type '{cfg.type}' is not valid.")
+ raise ValueError(f"The motor type '{cfg.type}' is not valid.")
return cameras
diff --git a/lerobot/common/robot_devices/control_utils.py b/lerobot/common/robot_devices/control_utils.py
index d2361a64..c5870e1f 100644
--- a/lerobot/common/robot_devices/control_utils.py
+++ b/lerobot/common/robot_devices/control_utils.py
@@ -113,46 +113,73 @@ def predict_action(observation, policy, device, use_amp):
return action
+# def init_keyboard_listener():
+# # Allow to exit early while recording an episode or resetting the environment,
+# # by tapping the right arrow key '->'. This might require a sudo permission
+# # to allow your terminal to monitor keyboard events.
+# events = {}
+# events["exit_early"] = False
+# events["rerecord_episode"] = False
+# events["stop_recording"] = False
+
+# if is_headless():
+# logging.warning(
+# "Headless environment detected. On-screen cameras display and keyboard inputs will not be available."
+# )
+# listener = None
+# return listener, events
+
+# # Only import pynput if not in a headless environment
+# from pynput import keyboard
+
+# def on_press(key):
+# try:
+# if key == keyboard.Key.right:
+# print("Right arrow key pressed. Exiting loop...")
+# events["exit_early"] = True
+# elif key == keyboard.Key.left:
+# print("Left arrow key pressed. Exiting loop and rerecord the last episode...")
+# events["rerecord_episode"] = True
+# events["exit_early"] = True
+# elif key == keyboard.Key.esc:
+# print("Escape key pressed. Stopping data recording...")
+# events["stop_recording"] = True
+# events["exit_early"] = True
+# except Exception as e:
+# print(f"Error handling key press: {e}")
+
+# listener = keyboard.Listener(on_press=on_press)
+# listener.start()
+
+# return listener, events
+
def init_keyboard_listener():
- # Allow to exit early while recording an episode or resetting the environment,
- # by tapping the right arrow key '->'. This might require a sudo permission
- # to allow your terminal to monitor keyboard events.
events = {}
events["exit_early"] = False
events["rerecord_episode"] = False
events["stop_recording"] = False
-
- if is_headless():
- logging.warning(
- "Headless environment detected. On-screen cameras display and keyboard inputs will not be available."
- )
- listener = None
- return listener, events
-
- # Only import pynput if not in a headless environment
- from pynput import keyboard
-
+ from sshkeyboard import listen_keyboard
+ import threading
def on_press(key):
try:
- if key == keyboard.Key.right:
+ if key == "right":
print("Right arrow key pressed. Exiting loop...")
events["exit_early"] = True
- elif key == keyboard.Key.left:
+ elif key == "left":
print("Left arrow key pressed. Exiting loop and rerecord the last episode...")
events["rerecord_episode"] = True
events["exit_early"] = True
- elif key == keyboard.Key.esc:
- print("Escape key pressed. Stopping data recording...")
+ elif key == "q":
+ print("Q key pressed. Stopping data recording...")
events["stop_recording"] = True
events["exit_early"] = True
except Exception as e:
print(f"Error handling key press: {e}")
- listener = keyboard.Listener(on_press=on_press)
+ listener = threading.Thread(target=listen_keyboard, kwargs={"on_press": on_press})
listener.start()
- return listener, events
-
+ return listener,events
def warmup_record(
robot,
@@ -256,7 +283,8 @@ def control_loop(
frame = {**observation, **action, "task": single_task}
dataset.add_frame(frame)
- if display_cameras and not is_headless():
+ if display_cameras:
+ # if display_cameras and not is_headless():
image_keys = [key for key in observation if "image" in key]
for key in image_keys:
cv2.imshow(key, cv2.cvtColor(observation[key].numpy(), cv2.COLOR_RGB2BGR))
@@ -288,17 +316,25 @@ def reset_environment(robot, events, reset_time_s, fps):
teleoperate=True,
)
+# def stop_recording(robot, listener, display_cameras):
+# robot.disconnect()
+
+# if not is_headless():
+# if listener is not None:
+# listener.stop()
+
+# if display_cameras:
+# cv2.destroyAllWindows()
def stop_recording(robot, listener, display_cameras):
robot.disconnect()
- if not is_headless():
- if listener is not None:
- listener.stop()
-
- if display_cameras:
- cv2.destroyAllWindows()
+ from sshkeyboard import stop_listening
+ if listener is not None:
+ stop_listening()
+ if display_cameras:
+ cv2.destroyAllWindows()
def sanity_check_dataset_name(repo_id, policy_cfg):
_, dataset_name = repo_id.split("/")
diff --git a/lerobot/common/robot_devices/robots/configs.py b/lerobot/common/robot_devices/robots/configs.py
index 88cb4e6f..ac38c7eb 100644
--- a/lerobot/common/robot_devices/robots/configs.py
+++ b/lerobot/common/robot_devices/robots/configs.py
@@ -479,6 +479,45 @@ class So100RobotConfig(ManipulatorRobotConfig):
mock: bool = False
+@RobotConfig.register_subclass("roarm_m3")
+@dataclass
+class RoarmRobotConfig(RobotConfig):
+ # `max_relative_target` limits the magnitude of the relative positional target vector for safety purposes.
+ # Set this to a positive scalar to have the same value for all motors, or a list that is the same length as
+ # the number of motors in your follower arms.
+ max_relative_target: int | None = None
+
+ leader_arms: dict[str, str] = field(
+ default_factory=lambda: {
+ "main": "/dev/ttyUSB0",
+ }
+ )
+
+ # Follower arms configuration: left and right ports
+ follower_arms: dict[str, str] = field(
+ default_factory=lambda: {
+ "main": "/dev/ttyUSB1",
+ }
+ )
+
+ cameras: dict[str, CameraConfig] = field(
+ default_factory=lambda: {
+ "laptop": OpenCVCameraConfig(
+ camera_index=0,
+ fps=30,
+ width=640,
+ height=480,
+ ),
+ "phone": OpenCVCameraConfig(
+ camera_index=1,
+ fps=30,
+ width=640,
+ height=480,
+ ),
+ }
+ )
+
+ mock: bool = False
@RobotConfig.register_subclass("stretch")
@dataclass
@@ -515,7 +554,6 @@ class StretchRobotConfig(RobotConfig):
mock: bool = False
-
@RobotConfig.register_subclass("lekiwi")
@dataclass
class LeKiwiRobotConfig(RobotConfig):
diff --git a/lerobot/common/robot_devices/robots/mobile_manipulator.py b/lerobot/common/robot_devices/robots/mobile_manipulator.py
index c2cad227..b20c61f7 100644
--- a/lerobot/common/robot_devices/robots/mobile_manipulator.py
+++ b/lerobot/common/robot_devices/robots/mobile_manipulator.py
@@ -392,19 +392,21 @@ class MobileManipulator:
for name in self.leader_arms:
pos = self.leader_arms[name].read("Present_Position")
pos_tensor = torch.from_numpy(pos).float()
+ # Instead of pos_tensor.item(), use tolist() to convert the entire tensor to a list
arm_positions.extend(pos_tensor.tolist())
- y_cmd = 0.0 # m/s forward/backward
- x_cmd = 0.0 # m/s lateral
+ # (The rest of your code for generating wheel commands remains unchanged)
+ x_cmd = 0.0 # m/s forward/backward
+ y_cmd = 0.0 # m/s lateral
theta_cmd = 0.0 # deg/s rotation
if self.pressed_keys["forward"]:
- y_cmd += xy_speed
- if self.pressed_keys["backward"]:
- y_cmd -= xy_speed
- if self.pressed_keys["left"]:
x_cmd += xy_speed
- if self.pressed_keys["right"]:
+ if self.pressed_keys["backward"]:
x_cmd -= xy_speed
+ if self.pressed_keys["left"]:
+ y_cmd += xy_speed
+ if self.pressed_keys["right"]:
+ y_cmd -= xy_speed
if self.pressed_keys["rotate_left"]:
theta_cmd += theta_speed
if self.pressed_keys["rotate_right"]:
@@ -582,8 +584,8 @@ class MobileManipulator:
# Create the body velocity vector [x, y, theta_rad].
velocity_vector = np.array([x_cmd, y_cmd, theta_rad])
- # Define the wheel mounting angles (defined from y axis cw)
- angles = np.radians(np.array([300, 180, 60]))
+ # Define the wheel mounting angles with a -90° offset.
+ angles = np.radians(np.array([240, 120, 0]) - 90)
# Build the kinematic matrix: each row maps body velocities to a wheel’s linear speed.
# The third column (base_radius) accounts for the effect of rotation.
m = np.array([[np.cos(a), np.sin(a), base_radius] for a in angles])
@@ -639,8 +641,8 @@ class MobileManipulator:
# Compute each wheel’s linear speed (m/s) from its angular speed.
wheel_linear_speeds = wheel_radps * wheel_radius
- # Define the wheel mounting angles (defined from y axis cw)
- angles = np.radians(np.array([300, 180, 60]))
+ # Define the wheel mounting angles with a -90° offset.
+ angles = np.radians(np.array([240, 120, 0]) - 90)
m = np.array([[np.cos(a), np.sin(a), base_radius] for a in angles])
# Solve the inverse kinematics: body_velocity = M⁻¹ · wheel_linear_speeds.
diff --git a/lerobot/common/robot_devices/robots/roarm_m3.py b/lerobot/common/robot_devices/robots/roarm_m3.py
new file mode 100644
index 00000000..24461194
--- /dev/null
+++ b/lerobot/common/robot_devices/robots/roarm_m3.py
@@ -0,0 +1,306 @@
+"""Contains logic to instantiate a robot, read information from its motors and cameras,
+and send orders to its motors.
+"""
+# TODO(rcadene, aliberts): reorganize the codebase into one file per robot, with the associated
+# calibration procedure, to make it easy for people to add their own robot.
+
+import json
+import logging
+import time
+import warnings
+from pathlib import Path
+
+import numpy as np
+import torch
+
+from lerobot.common.robot_devices.cameras.utils import make_cameras_from_configs
+from lerobot.common.robot_devices.robots.configs import RoarmRobotConfig
+from lerobot.common.robot_devices.utils import RobotDeviceAlreadyConnectedError, RobotDeviceNotConnectedError
+from roarm_sdk.roarm import roarm
+
+def ensure_safe_goal_position(
+ goal_pos: torch.Tensor, present_pos: torch.Tensor, max_relative_target: float | list[float]
+):
+ # Cap relative action target magnitude for safety.
+ diff = goal_pos - present_pos
+ max_relative_target = torch.tensor(max_relative_target)
+ safe_diff = torch.minimum(diff, max_relative_target)
+ safe_diff = torch.maximum(safe_diff, -max_relative_target)
+ safe_goal_pos = present_pos + safe_diff
+
+ if not torch.allclose(goal_pos, safe_goal_pos):
+ logging.warning(
+ "Relative goal position magnitude had to be clamped to be safe.\n"
+ f" requested relative goal position target: {diff}\n"
+ f" clamped relative goal position target: {safe_diff}"
+ )
+
+ return safe_goal_pos
+
+def make_roarm_from_configs(configs: dict[str, str]) -> (dict[str, roarm]):
+ roarms = {}
+
+ for key, port in configs.items():
+ roarms[key] = roarm(roarm_type="roarm_m3", port=port, baudrate=115200)
+
+ return roarms
+
+class RoarmRobot:
+
+ def __init__(
+ self,
+ config: RoarmRobotConfig,
+ ):
+ self.config = config
+ self.robot_type = self.config.type
+ self.leader_arms = make_roarm_from_configs(self.config.leader_arms)
+ self.follower_arms = make_roarm_from_configs(self.config.follower_arms)
+ self.cameras = make_cameras_from_configs(self.config.cameras)
+ self.is_connected = False
+ self.logs = {}
+
+ @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:
+ return {
+ "action": {
+ "dtype": "float32",
+ "shape": (6,),
+ "names": "roam_m3",
+ },
+ "observation.state": {
+ "dtype": "float32",
+ "shape": (6,),
+ "names": "roam_m3",
+ },
+ }
+
+ @property
+ def features(self):
+ return {**self.motor_features, **self.camera_features}
+
+ @property
+ def has_camera(self):
+ return len(self.cameras) > 0
+
+ @property
+ def num_cameras(self):
+ return len(self.cameras)
+
+ def connect(self):
+ if self.is_connected:
+ raise RobotDeviceAlreadyConnectedError(
+ "RoarmRobot is already connected. Do not run `robot.connect()` twice."
+ )
+
+ if not self.leader_arms and not self.follower_arms and not self.cameras:
+ raise ValueError(
+ "RoarmRobot doesn't have any device to connect. See example of usage in docstring of the class."
+ )
+
+ for name in self.follower_arms:
+ self.follower_arms[name].joints_angle_get()
+ for name in self.leader_arms:
+ self.leader_arms[name].joints_angle_get()
+
+ # Connect the cameras
+ for name in self.cameras:
+ self.cameras[name].connect()
+
+ self.is_connected = True
+
+ def teleop_step(
+ self, record_data=False
+ ) -> None | tuple[dict[str, torch.Tensor], dict[str, torch.Tensor]]:
+ if not self.is_connected:
+ raise RobotDeviceNotConnectedError(
+ "RoarmRobot is not connected. You need to run `robot.connect()`."
+ )
+
+ # Prepare to assign the position of the leader to the follower
+ leader_pos = {}
+ for name in self.leader_arms:
+ before_lread_t = time.perf_counter()
+ leader_pos[name] = np.array(self.leader_arms[name].joints_angle_get(), dtype=np.float32)
+ leader_pos[name] = torch.from_numpy(leader_pos[name])
+ self.logs[f"read_leader_{name}_pos_dt_s"] = time.perf_counter() - before_lread_t
+
+ # Send goal position to the follower
+ follower_goal_pos = {}
+ for name in self.follower_arms:
+ before_fwrite_t = time.perf_counter()
+ goal_pos = leader_pos[name]
+
+ # Cap goal position when too far away from present position.
+ # Slower fps expected due to reading from the follower.
+ if self.config.max_relative_target is not None:
+ present_pos = np.array(self.follower_arms[name].joints_angle_get(), dtype=np.float32)
+ present_pos = torch.from_numpy(present_pos)
+ goal_pos = ensure_safe_goal_position(goal_pos, present_pos, self.config.max_relative_target)
+
+ # Used when record_data=True
+ follower_goal_pos[name] = goal_pos
+
+ goal_pos = goal_pos.numpy().astype(np.int32)
+ goal_pos = goal_pos.tolist() if isinstance(goal_pos, (np.ndarray, torch.Tensor)) else goal_pos
+ self.follower_arms[name].joints_angle_ctrl(angles=goal_pos, speed=0, acc=0)
+ self.logs[f"write_follower_{name}_goal_pos_dt_s"] = time.perf_counter() - before_fwrite_t
+
+ # Early exit when recording data is not requested
+ if not record_data:
+ return
+
+ # TODO(rcadene): Add velocity and other info
+ # Read follower position
+ follower_pos = {}
+ for name in self.follower_arms:
+ before_fread_t = time.perf_counter()
+ follower_pos[name] = np.array(self.follower_arms[name].joints_angle_get(), dtype=np.float32)
+ follower_pos[name] = torch.from_numpy(follower_pos[name])
+ self.logs[f"read_follower_{name}_pos_dt_s"] = time.perf_counter() - before_fread_t
+
+ # Create state by concatenating follower current position
+ state = []
+ for name in self.follower_arms:
+ if name in follower_pos:
+ state.append(follower_pos[name])
+ state = torch.cat(state)
+
+ # Create action by concatenating follower goal position
+ action = []
+ for name in self.follower_arms:
+ if name in follower_goal_pos:
+ action.append(follower_goal_pos[name])
+ action = torch.cat(action)
+
+ # Capture images from cameras
+ images = {}
+ for name in self.cameras:
+ before_camread_t = time.perf_counter()
+ images[name] = self.cameras[name].async_read()
+ images[name] = torch.from_numpy(images[name])
+ self.logs[f"read_camera_{name}_dt_s"] = self.cameras[name].logs["delta_timestamp_s"]
+ self.logs[f"async_read_camera_{name}_dt_s"] = time.perf_counter() - before_camread_t
+
+ # Populate output dictionaries
+ obs_dict, action_dict = {}, {}
+ obs_dict["observation.state"] = state
+ action_dict["action"] = action
+ for name in self.cameras:
+ obs_dict[f"observation.images.{name}"] = images[name]
+
+ return obs_dict, action_dict
+
+ def capture_observation(self):
+ """The returned observations do not have a batch dimension."""
+ if not self.is_connected:
+ raise RobotDeviceNotConnectedError(
+ "RoarmRobot is not connected. You need to run `robot.connect()`."
+ )
+
+ # Read follower position
+ follower_pos = {}
+ for name in self.follower_arms:
+ before_fread_t = time.perf_counter()
+ follower_pos[name] = np.array(self.follower_arms[name].joints_angle_get(), dtype=np.float32)
+ follower_pos[name] = torch.from_numpy(follower_pos[name])
+ self.logs[f"read_follower_{name}_pos_dt_s"] = time.perf_counter() - before_fread_t
+
+ # Create state by concatenating follower current position
+ state = []
+ for name in self.follower_arms:
+ if name in follower_pos:
+ state.append(follower_pos[name])
+ state = torch.cat(state)
+
+ # Capture images from cameras
+ images = {}
+ for name in self.cameras:
+ before_camread_t = time.perf_counter()
+ images[name] = self.cameras[name].async_read()
+ images[name] = torch.from_numpy(images[name])
+ self.logs[f"read_camera_{name}_dt_s"] = self.cameras[name].logs["delta_timestamp_s"]
+ self.logs[f"async_read_camera_{name}_dt_s"] = time.perf_counter() - before_camread_t
+
+ # Populate output dictionaries and format to pytorch
+ obs_dict = {}
+ obs_dict["observation.state"] = state
+ for name in self.cameras:
+ obs_dict[f"observation.images.{name}"] = images[name]
+ return obs_dict
+
+ def send_action(self, action: torch.Tensor) -> torch.Tensor:
+ """Command the follower arms to move to a target joint configuration.
+
+ The relative action magnitude may be clipped depending on the configuration parameter
+ `max_relative_target`. In this case, the action sent differs from original action.
+ Thus, this function always returns the action actually sent.
+
+ Args:
+ action: tensor containing the concatenated goal positions for the follower arms.
+ """
+ if not self.is_connected:
+ raise RobotDeviceNotConnectedError(
+ "RoarmRobot is not connected. You need to run `robot.connect()`."
+ )
+
+ from_idx = 0
+ to_idx = 6
+ action_sent = []
+ for name in self.follower_arms:
+ # Get goal position of each follower arm by splitting the action vector
+ goal_pos = action[from_idx:to_idx]
+ from_idx = to_idx
+
+ # Cap goal position when too far away from present position.
+ # Slower fps expected due to reading from the follower.
+ if self.config.max_relative_target is not None:
+ present_pos = np.array(self.follower_arms[name].joints_angle_get(), dtype=np.float32)
+ present_pos = torch.from_numpy(present_pos)
+ goal_pos = ensure_safe_goal_position(goal_pos, present_pos, self.config.max_relative_target)
+
+ # Save tensor to concat and return
+ action_sent.append(goal_pos)
+
+ # Send goal position to each follower
+ goal_pos = goal_pos.numpy().astype(np.int32)
+ goal_pos = goal_pos.tolist() if isinstance(goal_pos, (np.ndarray, torch.Tensor)) else goal_pos
+ self.follower_arms[name].joints_angle_ctrl(angles=goal_pos, speed=0, acc=0)
+
+ return torch.cat(action_sent)
+
+ def print_logs(self):
+ pass
+ # TODO(aliberts): move robot-specific logs logic here
+
+ def disconnect(self):
+ if not self.is_connected:
+ raise RobotDeviceNotConnectedError(
+ "RoarmRobot is not connected. You need to run `robot.connect()` before disconnecting."
+ )
+
+ for name in self.follower_arms:
+ self.follower_arms[name].disconnect()
+
+ for name in self.leader_arms:
+ self.leader_arms[name].disconnect()
+
+ for name in self.cameras:
+ self.cameras[name].disconnect()
+
+ self.is_connected = False
+
+ def __del__(self):
+ if getattr(self, "is_connected", False):
+ self.disconnect()
diff --git a/lerobot/common/robot_devices/robots/utils.py b/lerobot/common/robot_devices/robots/utils.py
index 47e2519b..d418ec34 100644
--- a/lerobot/common/robot_devices/robots/utils.py
+++ b/lerobot/common/robot_devices/robots/utils.py
@@ -9,6 +9,7 @@ from lerobot.common.robot_devices.robots.configs import (
MossRobotConfig,
RobotConfig,
So100RobotConfig,
+ RoarmRobotConfig,
StretchRobotConfig,
)
@@ -44,6 +45,8 @@ def make_robot_config(robot_type: str, **kwargs) -> RobotConfig:
return MossRobotConfig(**kwargs)
elif robot_type == "so100":
return So100RobotConfig(**kwargs)
+ elif robot_type == "roarm_m3":
+ return RoarmRobotConfig(**kwargs)
elif robot_type == "stretch":
return StretchRobotConfig(**kwargs)
elif robot_type == "lekiwi":
@@ -61,12 +64,15 @@ def make_robot_from_config(config: RobotConfig):
from lerobot.common.robot_devices.robots.mobile_manipulator import MobileManipulator
return MobileManipulator(config)
+ elif isinstance(config, RoarmRobotConfig):
+ from lerobot.common.robot_devices.robots.roarm_m3 import RoarmRobot
+
+ return RoarmRobot(config)
else:
from lerobot.common.robot_devices.robots.stretch import StretchRobot
return StretchRobot(config)
-
def make_robot(robot_type: str, **kwargs) -> Robot:
config = make_robot_config(robot_type, **kwargs)
return make_robot_from_config(config)
diff --git a/lerobot/common/utils/utils.py b/lerobot/common/utils/utils.py
index cd26f04b..d0c12b30 100644
--- a/lerobot/common/utils/utils.py
+++ b/lerobot/common/utils/utils.py
@@ -17,7 +17,6 @@ import logging
import os
import os.path as osp
import platform
-import subprocess
from copy import copy
from datetime import datetime, timezone
from pathlib import Path
@@ -166,31 +165,23 @@ def capture_timestamp_utc():
def say(text, blocking=False):
- system = platform.system()
-
- if system == "Darwin":
- cmd = ["say", text]
-
- elif system == "Linux":
- cmd = ["spd-say", text]
+ # Check if mac, linux, or windows.
+ if platform.system() == "Darwin":
+ cmd = f'say "{text}"'
+ if not blocking:
+ cmd += " &"
+ elif platform.system() == "Linux":
+ cmd = f'spd-say "{text}"'
if blocking:
- cmd.append("--wait")
+ cmd += " --wait"
+ elif platform.system() == "Windows":
+ # TODO(rcadene): Make blocking option work for Windows
+ cmd = (
+ 'PowerShell -Command "Add-Type -AssemblyName System.Speech; '
+ f"(New-Object System.Speech.Synthesis.SpeechSynthesizer).Speak('{text}')\""
+ )
- elif system == "Windows":
- cmd = [
- "PowerShell",
- "-Command",
- "Add-Type -AssemblyName System.Speech; "
- f"(New-Object System.Speech.Synthesis.SpeechSynthesizer).Speak('{text}')",
- ]
-
- else:
- raise RuntimeError("Unsupported operating system for text-to-speech.")
-
- if blocking:
- subprocess.run(cmd, check=True)
- else:
- subprocess.Popen(cmd, creationflags=subprocess.CREATE_NO_WINDOW if system == "Windows" else 0)
+ os.system(cmd)
def log_say(text, play_sounds, blocking=False):
diff --git a/lerobot/scripts/control_robot.py b/lerobot/scripts/control_robot.py
index ab5d0e8a..32271b80 100644
--- a/lerobot/scripts/control_robot.py
+++ b/lerobot/scripts/control_robot.py
@@ -259,6 +259,7 @@ def record(
if not robot.is_connected:
robot.connect()
+ #listener, events = init_keyboard_listener()
listener, events = init_keyboard_listener()
# Execute a few seconds without recording to:
@@ -314,7 +315,9 @@ def record(
if events["stop_recording"]:
break
- log_say("Stop recording", cfg.play_sounds, blocking=True)
+ # log_say("Stop recording", cfg.play_sounds, blocking=True)
+ log_say("Stop recording", cfg.play_sounds)
+
stop_recording(robot, listener, cfg.display_cameras)
if cfg.push_to_hub:
diff --git a/lerobot/scripts/eval.py b/lerobot/scripts/eval.py
index 47225993..a4f79afc 100644
--- a/lerobot/scripts/eval.py
+++ b/lerobot/scripts/eval.py
@@ -454,7 +454,7 @@ def _compile_episode_data(
@parser.wrap()
-def eval_main(cfg: EvalPipelineConfig):
+def eval(cfg: EvalPipelineConfig):
logging.info(pformat(asdict(cfg)))
# Check device is available
@@ -499,4 +499,4 @@ def eval_main(cfg: EvalPipelineConfig):
if __name__ == "__main__":
init_logging()
- eval_main()
+ eval()
diff --git a/lerobot/scripts/visualize_dataset_html.py b/lerobot/scripts/visualize_dataset_html.py
index d5825aa6..a0da0869 100644
--- a/lerobot/scripts/visualize_dataset_html.py
+++ b/lerobot/scripts/visualize_dataset_html.py
@@ -158,7 +158,7 @@ def run_server(
if major_version < 2:
return "Make sure to convert your LeRobotDataset to v2 & above."
- episode_data_csv_str, columns, ignored_columns = get_episode_data(dataset, episode_id)
+ episode_data_csv_str, columns = get_episode_data(dataset, episode_id)
dataset_info = {
"repo_id": f"{dataset_namespace}/{dataset_name}",
"num_samples": dataset.num_frames
@@ -194,7 +194,7 @@ def run_server(
]
response = requests.get(
- f"https://huggingface.co/datasets/{repo_id}/resolve/main/meta/episodes.jsonl", timeout=5
+ f"https://huggingface.co/datasets/{repo_id}/resolve/main/meta/episodes.jsonl"
)
response.raise_for_status()
# Split into lines and parse each line as JSON
@@ -218,7 +218,6 @@ def run_server(
videos_info=videos_info,
episode_data_csv_str=episode_data_csv_str,
columns=columns,
- ignored_columns=ignored_columns,
)
app.run(host=host, port=port)
@@ -237,14 +236,6 @@ def get_episode_data(dataset: LeRobotDataset | IterableNamespace, episode_index)
selected_columns = [col for col, ft in dataset.features.items() if ft["dtype"] == "float32"]
selected_columns.remove("timestamp")
- ignored_columns = []
- for column_name in selected_columns:
- shape = dataset.features[column_name]["shape"]
- shape_dim = len(shape)
- if shape_dim > 1:
- selected_columns.remove(column_name)
- ignored_columns.append(column_name)
-
# init header of csv with state and action names
header = ["timestamp"]
@@ -300,7 +291,7 @@ def get_episode_data(dataset: LeRobotDataset | IterableNamespace, episode_index)
csv_writer.writerows(rows)
csv_string = csv_buffer.getvalue()
- return csv_string, columns, ignored_columns
+ return csv_string, columns
def get_episode_video_paths(dataset: LeRobotDataset, ep_index: int) -> list[str]:
@@ -327,9 +318,7 @@ def get_episode_language_instruction(dataset: LeRobotDataset, ep_index: int) ->
def get_dataset_info(repo_id: str) -> IterableNamespace:
- response = requests.get(
- f"https://huggingface.co/datasets/{repo_id}/resolve/main/meta/info.json", timeout=5
- )
+ response = requests.get(f"https://huggingface.co/datasets/{repo_id}/resolve/main/meta/info.json")
response.raise_for_status() # Raises an HTTPError for bad responses
dataset_info = response.json()
dataset_info["repo_id"] = repo_id
diff --git a/lerobot/templates/visualize_dataset_template.html b/lerobot/templates/visualize_dataset_template.html
index cf9d40f1..d81ce630 100644
--- a/lerobot/templates/visualize_dataset_template.html
+++ b/lerobot/templates/visualize_dataset_template.html
@@ -42,22 +42,22 @@
-
-
+
-
-
-
+
-
@@ -83,7 +83,7 @@
-
@@ -224,58 +224,49 @@
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
+
+
+
+
+
-
-
-
- {% if ignored_columns|length > 0 %}
-
- Columns {{ ignored_columns }} are NOT shown since the visualizer currently does not support 2D or 3D data.
-
- {% endif %}
+
-
@@ -485,7 +476,7 @@
episodes: {{ episodes }},
pageSize: 100,
page: 1,
-
+
init() {
// Find which page contains the current episode_id
const currentEpisodeId = {{ episode_id }};
@@ -494,23 +485,23 @@
this.page = Math.floor(episodeIndex / this.pageSize) + 1;
}
},
-
+
get totalPages() {
return Math.ceil(this.episodes.length / this.pageSize);
},
-
+
get paginatedEpisodes() {
const start = (this.page - 1) * this.pageSize;
const end = start + this.pageSize;
return this.episodes.slice(start, end);
},
-
+
nextPage() {
if (this.page < this.totalPages) {
this.page++;
}
},
-
+
prevPage() {
if (this.page > 1) {
this.page--;
@@ -524,7 +515,7 @@
window.addEventListener('keydown', (e) => {
// Use the space bar to play and pause, instead of default action (e.g. scrolling)
const { keyCode, key } = e;
-
+
if (keyCode === 32 || key === ' ') {
e.preventDefault();
const btnPause = document.querySelector('[x-ref="btnPause"]');