diff --git a/README.md b/README.md index 57fbf2a..c587800 100644 --- a/README.md +++ b/README.md @@ -8,6 +8,9 @@ Below is a list of all tutorials available in this repository: ### [Foxglove Visualization for 1X World Model Challenge](datasets/1x_eve/README.md) - 📝 Use Foxglove to visualize 1X World Model Challenge - 🎥 [Video](https://www.youtube.com/watch?v=A9wl491ltPA) +### [EuRoC MAV Dataset in Foxglove](datasets/EuRoC_MAV/README.md) +- 📝 Drone SLAM of the MH01 Environment from EuRoC MAV +- 🔗 [Related Blog Post](https://foxglove.dev/blog/converting-euroc-mav-dataset-to-mcap) ### [Convert .mat files to MCAP](datasets/NASA_mat_to_MCAP/README.md) - 📝 Visualize Matlab files for NASA Valkyrie box pickup task ### [Converting Argoverse 2 Dataset to MCAP](datasets/foxglove_av2_tutorial/README.md) diff --git a/datasets/EuRoC_MAV/.gitignore b/datasets/EuRoC_MAV/.gitignore new file mode 100644 index 0000000..999ef30 --- /dev/null +++ b/datasets/EuRoC_MAV/.gitignore @@ -0,0 +1,3 @@ +*.mcap +data/* +.env \ No newline at end of file diff --git a/datasets/EuRoC_MAV/README.md b/datasets/EuRoC_MAV/README.md new file mode 100644 index 0000000..cbdeec8 --- /dev/null +++ b/datasets/EuRoC_MAV/README.md @@ -0,0 +1,45 @@ +--- +title: "EuRoC MAV Dataset in Foxglove" +short_description: "Drone SLAM of the MH01 Environment from EuRoC MAV" +blog_post_url: "https://foxglove.dev/blog/converting-euroc-mav-dataset-to-mcap" +--- + +# EuRoC MAV Dataset in Foxglove + +This tutorial shows how to convert the EuRoC MAV dataset into an MCAP file for visualization in Foxglove. + +![SLAM_gif](media/MH01_Final_gif_cut.gif) + +## Run this tutorial locally: +1. Download one of the EuRoC environments from [ETH Zurich](https://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets) in ASL format. The Machine Hall 01 set is visualized in the tutorial. +2. Make sure to have a working [ROS distribution](https://docs.ros.org/en/humble/Installation.html) and install dependancies: +```bash +sudo apt install \ + ros-$ROS_DISTRO-foxglove-bridge \ + ros-$ROS_DISTRO-imu-tools \ + ros-$ROS_DISTRO-rtabmap-ros \ + ros-$ROS_DISTRO-rosbag2-storage-mcap \ + ros-$ROS_DISTRO-image-proc +``` +In a new python environment, install: +```bash +pip install foxglove-sdk numpy opencv-python pyyaml +``` +3. Convert the dataset to MCAP +```bash +python3 convert-euroc-2-mcap.py --src --dst .mcap +``` +4. Build the ROS 2 package called euroc_slam +```bash +cd ~/tutorials/EuRoC_MAV/ros2_ws +colcon build --symlink-install +source install/setup.bash +``` +5. Run SLAM and visualize in Foxglove while the dataset plays back: +```bash +ros2 launch euroc_slam firefly.launch.py +``` +In a seperate terminal: +```bash +ros2 bag play --clock +``` diff --git a/datasets/EuRoC_MAV/convert-euroc-2-mcap.py b/datasets/EuRoC_MAV/convert-euroc-2-mcap.py new file mode 100644 index 0000000..64da38b --- /dev/null +++ b/datasets/EuRoC_MAV/convert-euroc-2-mcap.py @@ -0,0 +1,180 @@ +import foxglove +import argparse +import os +import csv +import cv2 +import yaml +import numpy as np +from foxglove import Schema, Channel +from sensor_msgs.msg import Image, Imu +from std_msgs.msg import Header +from geometry_msgs.msg import Quaternion, Vector3 +from rclpy.serialization import serialize_message +from pathlib import Path + + +def get_image_msg(img_path: str, timestamp: int, cam_num: int) -> Image: + # Stereo images should be loaded in as grayscale + img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE) + if img is None: + raise ValueError(f"Could not load image: {img_path}") + + height, width = img.shape + + sec = int(timestamp // 1e9) + nsec = int(timestamp % 1e9) + + # Populate the image message data + ros_image = Image() + ros_image.header = Header() + ros_image.header.stamp.sec = sec + ros_image.header.stamp.nanosec = nsec + ros_image.header.frame_id = f"cam{cam_num}" + ros_image.height = height + ros_image.width = width + ros_image.encoding = "mono8" # Stereo images + ros_image.step = width # For mono8, 1 byte per pixel + ros_image.data = img.tobytes() + + return ros_image + + +def read_images(cam_directory: str, channel: Channel, cam_num: int) -> None: + # Loop through the data.csv file and read in the image files + csv_path = os.path.join(cam_directory, "data.csv") + with open(csv_path, "r") as csv_file: + reader = csv.reader(csv_file) + next(reader) # Skip the first row with headers + for row in reader: + timestamp = int(row[0]) + image_name = row[1] + image_path = os.path.join(cam_directory, "data", image_name) + if not os.path.exists(image_path): + print(f"Image {image_path} does not exist") + continue + + # Convert image to ROS2 message and write to channel + image_msg = get_image_msg(image_path, timestamp, cam_num) + channel.log(serialize_message(image_msg), log_time=timestamp) + + +def read_imu(imu_data_path: str, imu_channel: Channel, imu_yaml_path: str) -> None: + """Read IMU data and write to MCAP channel. + + IMU data is in the format: + timestamp [ns],w_RS_S_x [rad s^-1],w_RS_S_y [rad s^-1],w_RS_S_z [rad s^-1],a_RS_S_x [m s^-2],a_RS_S_y [m s^-2],a_RS_S_z [m s^-2] + + We will convert this to a custom IMU message that interfaces with sensor_msgs/msgs/Imu. + This will be in the form: + - header (header) + - orientation (quaternion) + - orientation covariance (float32[9]) + - angular velocity (vector3) + - angular velocity covariance (float32[9]) + - linear acceleration (vector3) + - linear acceleration covariance (float32[9]) + + Args: + imu_data_path: Path to IMU data CSV file + imu_channel: MCAP channel to write IMU messages to + imu_yaml_path: Path to IMU configuration YAML file + """ + # Get the IMU config with covariance information + with open(imu_yaml_path, "r") as imu_yaml_file: + imu_yaml = yaml.load(imu_yaml_file, Loader=yaml.FullLoader) + + # Get the noise and bias parameters, see https://github.com/ethz-asl/kalibr/wiki/IMU-Noise-Model for more details + sample_sqr_dt = np.sqrt(1.0 / float(imu_yaml["rate_hz"])) + sigma_gd = imu_yaml["gyroscope_noise_density"] * sample_sqr_dt + sigma_ad = imu_yaml["accelerometer_noise_density"] * sample_sqr_dt + + # Calculate the covariance matrices + orientation_cov = np.zeros((3, 3), dtype=np.float64) + angular_velocity_cov = np.diag([sigma_gd**2, sigma_gd**2, sigma_gd**2]).astype(np.float64) + linear_acceleration_cov = np.diag([sigma_ad**2, sigma_ad**2, sigma_ad**2]).astype(np.float64) + + with open(imu_data_path, "r") as imu_file: + reader = csv.reader(imu_file) + next(reader) # Skip the first row with headers + for row in reader: + timestamp = int(row[0]) + angular_velocity = [float(row[1]), float(row[2]), float(row[3])] + linear_acceleration = [float(row[4]), float(row[5]), float(row[6])] + + imu_msg = Imu() + imu_msg.header = Header() + imu_msg.header.stamp.sec = timestamp // int(1e9) + imu_msg.header.stamp.nanosec = timestamp % int(1e9) + imu_msg.header.frame_id = "imu4" # Transformation reference frame + # Orientation + imu_msg.orientation = Quaternion() + imu_msg.orientation.x = 0.0 + imu_msg.orientation.y = 0.0 + imu_msg.orientation.z = 0.0 + imu_msg.orientation.w = 1.0 + imu_msg.orientation_covariance = list(orientation_cov.flatten(order="C").astype(float)) + # Angular velocity + imu_msg.angular_velocity = Vector3() + imu_msg.angular_velocity.x = angular_velocity[0] + imu_msg.angular_velocity.y = angular_velocity[1] + imu_msg.angular_velocity.z = angular_velocity[2] + imu_msg.angular_velocity_covariance = list(angular_velocity_cov.flatten(order="C").astype(float)) + # Linear acceleration + imu_msg.linear_acceleration = Vector3() + imu_msg.linear_acceleration.x = linear_acceleration[0] + imu_msg.linear_acceleration.y = linear_acceleration[1] + imu_msg.linear_acceleration.z = linear_acceleration[2] + imu_msg.linear_acceleration_covariance = list(linear_acceleration_cov.flatten(order="C").astype(float)) + + imu_channel.log(serialize_message(imu_msg), log_time=timestamp) + + +def main() -> None: + parser = argparse.ArgumentParser(description='Convert Euroc dataset to MCAP format') + parser.add_argument('--src', type=str, required=True, help='Path to the Euroc dataset directory') + parser.add_argument('--dst', type=str, required=True, help='Path to the output MCAP file') + args = parser.parse_args() + + out_mcap_path = args.dst + if os.path.exists(out_mcap_path): # Remove the previous file if it already exists + os.remove(out_mcap_path) + + writer = foxglove.open_mcap(out_mcap_path, allow_overwrite=True) # Open the mcap file for writing + + imu_msg_path = Path("msgs/imu_flat.msg") + img_msg_path = Path("msgs/image_flat.msg") + + img_schema = Schema( + name="sensor_msgs/msg/Image", + encoding="ros2msg", + data=img_msg_path.read_bytes(), + ) + imu_schema = Schema( + name="sensor_msgs/msg/Imu", + encoding="ros2msg", + data=imu_msg_path.read_bytes(), + ) + + # ros2msg channels require cdr encoding type + cam0_channel = Channel(topic="/cam0/image_raw", schema=img_schema, message_encoding="cdr") + cam1_channel = Channel(topic="/cam1/image_raw", schema=img_schema, message_encoding="cdr") + imu_channel = Channel(topic="/imu0", schema=imu_schema, message_encoding="cdr") + + # Read in the data.csv file + data_csv_path = os.path.join(args.src, "data.csv") + cam0_dir = os.path.join(args.src, "cam0") + cam1_dir = os.path.join(args.src, "cam1") + imu_dir = os.path.join(args.src, "imu0", "data.csv") + imu_yaml_path = os.path.join(args.src, "imu0", "sensor.yaml") + + read_images(cam0_dir, cam0_channel, 0) + print("Done writing cam0") + 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a/datasets/EuRoC_MAV/msgs/image_flat.msg b/datasets/EuRoC_MAV/msgs/image_flat.msg new file mode 100644 index 0000000..90b1f50 --- /dev/null +++ b/datasets/EuRoC_MAV/msgs/image_flat.msg @@ -0,0 +1,19 @@ +================================================================================ +MSG: builtin_interfaces/Time +int32 sec +uint32 nanosec + +================================================================================ +MSG: std_msgs/Header +builtin_interfaces/Time stamp +string frame_id + +================================================================================ +MSG: sensor_msgs/Image +std_msgs/Header header +uint32 height +uint32 width +string encoding +uint8 is_bigendian +uint32 step +uint8[] data \ No newline at end of file diff --git a/datasets/EuRoC_MAV/msgs/imu_flat.msg b/datasets/EuRoC_MAV/msgs/imu_flat.msg new file mode 100644 index 0000000..dd9a253 --- /dev/null +++ b/datasets/EuRoC_MAV/msgs/imu_flat.msg @@ -0,0 +1,32 @@ +================================================================================ +MSG: geometry_msgs/Vector3 +float64 x +float64 y +float64 z + +================================================================================ +MSG: geometry_msgs/Quaternion +float64 x 0 +float64 y 0 +float64 z 0 +float64 w 1 + +================================================================================ +MSG: builtin_interfaces/Time +int32 sec +uint32 nanosec + +================================================================================ +MSG: std_msgs/Header +builtin_interfaces/Time stamp +string frame_id + +================================================================================ +MSG: sensor_msgs/Imu +std_msgs/Header header +geometry_msgs/Quaternion orientation +float64[9] orientation_covariance # Row major about x, y, z axes +geometry_msgs/Vector3 angular_velocity +float64[9] angular_velocity_covariance # Row major about x, y, z axes +geometry_msgs/Vector3 linear_acceleration +float64[9] linear_acceleration_covariance # Row major x, y z diff --git a/datasets/EuRoC_MAV/ros2_ws/.gitignore b/datasets/EuRoC_MAV/ros2_ws/.gitignore new file mode 100644 index 0000000..29cad58 --- /dev/null +++ b/datasets/EuRoC_MAV/ros2_ws/.gitignore @@ -0,0 +1,3 @@ +build/ +install/ +log/ \ No newline at end of file diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/LICENSE b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/LICENSE new file mode 100644 index 0000000..d645695 --- /dev/null +++ b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/LICENSE @@ -0,0 +1,202 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + 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. diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/euroc_slam/__init__.py b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/euroc_slam/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/euroc_slam/__pycache__/__init__.cpython-310.pyc b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/euroc_slam/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000..b61377c Binary files /dev/null and b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/euroc_slam/__pycache__/__init__.cpython-310.pyc differ diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/euroc_slam/__pycache__/firefly_state_publisher.cpython-310.pyc b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/euroc_slam/__pycache__/firefly_state_publisher.cpython-310.pyc new file mode 100644 index 0000000..df88dac Binary files /dev/null and b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/euroc_slam/__pycache__/firefly_state_publisher.cpython-310.pyc differ diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/euroc_slam/firefly_state_publisher.py b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/euroc_slam/firefly_state_publisher.py new file mode 100644 index 0000000..97d265d --- /dev/null +++ b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/euroc_slam/firefly_state_publisher.py @@ -0,0 +1,68 @@ +#!/usr/bin/env python3 +import rclpy +from rclpy.node import Node +from sensor_msgs.msg import JointState +import math + +class StatePublisher(Node): + def __init__(self): + super().__init__('firefly_state_publisher') + + # 1) spin_rate in revolutions per second + self.declare_parameter('spin_rate', 10.0) + self.spin_rate = self.get_parameter('spin_rate').get_parameter_value().double_value + + # 2) We’ll update at 30 Hz + self.update_hz = 30.0 + period = 1.0 / self.update_hz + + # 3) Precompute angular velocity (rad/s) and per‑tick increment + self.ang_vel = 2 * math.pi * self.spin_rate # rad/s + self.increment = self.ang_vel * period # rad per update + + # 4) JointState publisher + self.joint_pub = self.create_publisher(JointState, 'joint_states', 10) + self.joint_state = JointState() + self.joint_state.name = [ + 'firefly_rotor_0_joint', + 'firefly_rotor_1_joint', + 'firefly_rotor_2_joint', + 'firefly_rotor_3_joint', + 'firefly_rotor_4_joint', + 'firefly_rotor_5_joint', + ] + + self.angle = 0.0 # current angle in radians + + # 5) Timer instead of manual loop + self.create_timer(period, self.timer_callback) + self.get_logger().info(f'StatePublisher started: spin_rate={self.spin_rate} Hz, update={self.update_hz} Hz') + + def timer_callback(self): + # advance angle and wrap to [0, 2π) + self.angle = (self.angle + self.increment) % (2 * math.pi) + + # stamp and publish + now = self.get_clock().now().to_msg() + self.joint_state.header.stamp = now + + # alternate spin direction on adjacent rotors + positions = [] + for i in range(len(self.joint_state.name)): + sign = 1.0 if (i % 2 == 0) else -1.0 + positions.append(sign * self.angle) + self.joint_state.position = positions + + self.joint_pub.publish(self.joint_state) + +def main(args=None): + rclpy.init(args=args) + node = StatePublisher() + try: + rclpy.spin(node) + finally: + node.destroy_node() + rclpy.shutdown() + +if __name__ == '__main__': + main() diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/launch/firefly.launch.py b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/launch/firefly.launch.py new file mode 100644 index 0000000..20f7c4e --- /dev/null +++ b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/launch/firefly.launch.py @@ -0,0 +1,68 @@ +from launch import LaunchDescription +from launch.actions import DeclareLaunchArgument, IncludeLaunchDescription, TimerAction +from launch.launch_description_sources import PythonLaunchDescriptionSource +from launch.substitutions import Command, LaunchConfiguration, PathJoinSubstitution +from launch_ros.actions import Node +from launch_ros.substitutions import FindPackageShare +from launch_ros.parameter_descriptions import ParameterValue + + +def generate_launch_description(): + use_sim_time = LaunchConfiguration('use_sim_time', default='false') + + # Load URDF file + urdf_file = PathJoinSubstitution([FindPackageShare('euroc_slam'), 'urdf', 'firefly.urdf']) + robot_description = ParameterValue(Command(['cat ', urdf_file]), value_type=str) + + # Create nodes + foxglove_bridge_node = Node( + package='foxglove_bridge', + executable='foxglove_bridge', + name='foxglove_bridge', + output='screen', + ) + + robot_state_publisher_node = Node( + package='robot_state_publisher', + executable='robot_state_publisher', + name='robot_state_publisher', + output='screen', + parameters=[{'use_sim_time': use_sim_time, 'robot_description': robot_description}] + ) + + static_transform_publisher_node = Node( + package='tf2_ros', + executable='static_transform_publisher', + name='static_transform_publisher', + output='screen', + arguments=['0', '0', '0', '0', '0', '0', 'base_link', 'firefly_base_link'] + ) + + firefly_state_publisher_node = Node( + package='euroc_slam', + executable='firefly_state_publisher', + name='firefly_state_publisher', + output='screen' + ) + + rtabmap_include = IncludeLaunchDescription( + PythonLaunchDescriptionSource([ + FindPackageShare('rtabmap_examples'), + '/launch/euroc_datasets.launch.py' + ]), + launch_arguments={ + 'gt': 'false' + }.items() + ) + + return LaunchDescription([ + DeclareLaunchArgument( + 'use_sim_time', + default_value='false', + description='Use simulation (Gazebo) clock if true'), + foxglove_bridge_node, + TimerAction(period=1.0, actions=[robot_state_publisher_node]), # 2 second delay + TimerAction(period=2.0, actions=[rtabmap_include]), + TimerAction(period=3.0, actions=[firefly_state_publisher_node]), + TimerAction(period=4.0, actions=[static_transform_publisher_node]) + ]) diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/meshes/firefly_purple.dae b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/meshes/firefly_purple.dae new file mode 100644 index 0000000..9c20216 --- /dev/null +++ b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/meshes/firefly_purple.dae @@ -0,0 +1,90 @@ + + + + + Blender User + Blender 4.4.3 commit date:2025-04-29, commit 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+ + + + + + + + + 1 0 0 0 0 7.54979e-8 -1 0 0 1 7.54979e-8 0 0 0 0 1 + + + + + + + + + + + + + + \ No newline at end of file diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/package.xml b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/package.xml new file mode 100644 index 0000000..7c5781a --- /dev/null +++ b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/package.xml @@ -0,0 +1,18 @@ + + + + euroc_slam + 0.0.0 + Convert the EuRoC MAV dataset to MCAP + Carson Kohlbrenner + Apache-2.0 + + ament_copyright + ament_flake8 + ament_pep257 + python3-pytest + + + ament_python + + diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/resource/euroc_slam b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/resource/euroc_slam new file mode 100644 index 0000000..e69de29 diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/setup.cfg b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/setup.cfg new file mode 100644 index 0000000..981db22 --- /dev/null +++ b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/setup.cfg @@ -0,0 +1,4 @@ +[develop] +script_dir=$base/lib/euroc_slam +[install] +install_scripts=$base/lib/euroc_slam diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/setup.py b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/setup.py new file mode 100644 index 0000000..e0987b5 --- /dev/null +++ b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/setup.py @@ -0,0 +1,28 @@ +import os +from glob import glob +from setuptools import find_packages, setup + +package_name = 'euroc_slam' + +setup( + name=package_name, + version='0.0.0', + packages=find_packages(exclude=['test']), + data_files=[ + ('share/ament_index/resource_index/packages', + ['resource/' + package_name]), + ('share/' + package_name, ['package.xml']), + (os.path.join('share', package_name, 'launch'), glob(os.path.join('launch', '*launch.[pxy][yma]*'))), + (os.path.join('share', package_name, 'urdf'), glob('urdf/*')), + (os.path.join('share', package_name, 'meshes'), glob('meshes/*')), + ], + install_requires=['setuptools'], + zip_safe=True, + maintainer='Foxglove', + license='Apache-2.0', + entry_points={ + 'console_scripts': [ + 'firefly_state_publisher = euroc_slam.firefly_state_publisher:main', + ], + }, +) diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/test/test_copyright.py b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/test/test_copyright.py new file mode 100644 index 0000000..97a3919 --- /dev/null +++ b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/test/test_copyright.py @@ -0,0 +1,25 @@ +# Copyright 2015 Open Source Robotics Foundation, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from ament_copyright.main import main +import pytest + + +# Remove the `skip` decorator once the source file(s) have a copyright header +@pytest.mark.skip(reason='No copyright header has been placed in the generated source file.') +@pytest.mark.copyright +@pytest.mark.linter +def test_copyright(): + rc = main(argv=['.', 'test']) + assert rc == 0, 'Found errors' diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/test/test_flake8.py b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/test/test_flake8.py new file mode 100644 index 0000000..27ee107 --- /dev/null +++ b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/test/test_flake8.py @@ -0,0 +1,25 @@ +# Copyright 2017 Open Source Robotics Foundation, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from ament_flake8.main import main_with_errors +import pytest + + +@pytest.mark.flake8 +@pytest.mark.linter +def test_flake8(): + rc, errors = main_with_errors(argv=[]) + assert rc == 0, \ + 'Found %d code style errors / warnings:\n' % len(errors) + \ + '\n'.join(errors) diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/test/test_pep257.py b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/test/test_pep257.py new file mode 100644 index 0000000..b234a38 --- /dev/null +++ b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/test/test_pep257.py @@ -0,0 +1,23 @@ +# Copyright 2015 Open Source Robotics Foundation, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from ament_pep257.main import main +import pytest + + +@pytest.mark.linter +@pytest.mark.pep257 +def test_pep257(): + rc = main(argv=['.', 'test']) + assert rc == 0, 'Found code style errors / warnings' diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/urdf/firefly.urdf b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/urdf/firefly.urdf new file mode 100644 index 0000000..6a0f8a6 --- /dev/null +++ b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/urdf/firefly.urdf @@ -0,0 +1,367 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly_base_link + 10 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly_rotor_0_joint + firefly_rotor_0 + ccw + 0.0125 + 0.025 + 838 + 8.54858e-06 + 0.016 + gazebo/command/motor_speed + 0 + 8.06428e-05 + 1e-06 + motor_speed/0 + 10 + + + + Gazebo/Red + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly_rotor_1_joint + firefly_rotor_1 + cw + 0.0125 + 0.025 + 838 + 8.54858e-06 + 0.016 + gazebo/command/motor_speed + 1 + 8.06428e-05 + 1e-06 + motor_speed/1 + 10 + + + + Gazebo/Blue + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly_rotor_2_joint + firefly_rotor_2 + ccw + 0.0125 + 0.025 + 838 + 8.54858e-06 + 0.016 + gazebo/command/motor_speed + 2 + 8.06428e-05 + 1e-06 + motor_speed/2 + 10 + + + + Gazebo/Blue + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly_rotor_3_joint + firefly_rotor_3 + cw + 0.0125 + 0.025 + 838 + 8.54858e-06 + 0.016 + gazebo/command/motor_speed + 3 + 8.06428e-05 + 1e-06 + motor_speed/3 + 10 + + + + Gazebo/Blue + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly_rotor_4_joint + firefly_rotor_4 + ccw + 0.0125 + 0.025 + 838 + 8.54858e-06 + 0.016 + gazebo/command/motor_speed + 4 + 8.06428e-05 + 1e-06 + motor_speed/4 + 10 + + + + Gazebo/Blue + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly_rotor_5_joint + firefly_rotor_5 + cw + 0.0125 + 0.025 + 838 + 8.54858e-06 + 0.016 + gazebo/command/motor_speed + 5 + 8.06428e-05 + 1e-06 + motor_speed/5 + 10 + + + + Gazebo/Red + + \ No newline at end of file diff --git a/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/urdf/firefly_url.urdf b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/urdf/firefly_url.urdf new file mode 100644 index 0000000..b4d31e5 --- /dev/null +++ b/datasets/EuRoC_MAV/ros2_ws/src/euroc_slam/urdf/firefly_url.urdf @@ -0,0 +1,367 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly/base_link + 10 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly/rotor_0_joint + firefly/rotor_0 + ccw + 0.0125 + 0.025 + 838 + 8.54858e-06 + 0.016 + gazebo/command/motor_speed + 0 + 8.06428e-05 + 1e-06 + motor_speed/0 + 10 + + + + Gazebo/Red + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly/rotor_1_joint + firefly/rotor_1 + cw + 0.0125 + 0.025 + 838 + 8.54858e-06 + 0.016 + gazebo/command/motor_speed + 1 + 8.06428e-05 + 1e-06 + motor_speed/1 + 10 + + + + Gazebo/Blue + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly/rotor_2_joint + firefly/rotor_2 + ccw + 0.0125 + 0.025 + 838 + 8.54858e-06 + 0.016 + gazebo/command/motor_speed + 2 + 8.06428e-05 + 1e-06 + motor_speed/2 + 10 + + + + Gazebo/Blue + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly/rotor_3_joint + firefly/rotor_3 + cw + 0.0125 + 0.025 + 838 + 8.54858e-06 + 0.016 + gazebo/command/motor_speed + 3 + 8.06428e-05 + 1e-06 + motor_speed/3 + 10 + + + + Gazebo/Blue + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly/rotor_4_joint + firefly/rotor_4 + ccw + 0.0125 + 0.025 + 838 + 8.54858e-06 + 0.016 + gazebo/command/motor_speed + 4 + 8.06428e-05 + 1e-06 + motor_speed/4 + 10 + + + + Gazebo/Blue + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + firefly + firefly/rotor_5_joint + firefly/rotor_5 + cw + 0.0125 + 0.025 + 838 + 8.54858e-06 + 0.016 + gazebo/command/motor_speed + 5 + 8.06428e-05 + 1e-06 + motor_speed/5 + 10 + + + + Gazebo/Red + + \ No newline at end of file diff --git a/datasets/EuRoC_MAV/tutorial.md b/datasets/EuRoC_MAV/tutorial.md new file mode 100644 index 0000000..01178d9 --- /dev/null +++ b/datasets/EuRoC_MAV/tutorial.md @@ -0,0 +1,395 @@ +# Visualizing SLAM using Foxglove +Foxglove is a data visualization app that uses the universal [MCAP](https://mcap.dev/) data format to streamline multimodal robotics workflows. Simultaneous localization and mapping (SLAM) is an excellent example of multimodal data fusion that combines videos from calibrated cameras and acceleration data from an inertial measurement unit (IMU) to map out the environment and determine where the robot is located through time. + +In this tutorial, we will demonstrate how to convert the [EuRoC MAV](https://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets) dataset into MCAP format and visualize it using Foxglove. + +![Drone Snapshot](media/slam_snapshot.png) + + +## Table of Contents +- [Visualizing SLAM using Foxglove](#visualizing-slam-using-foxglove) + - [Step 1: Install Dependencies](#step-1-install-dependencies) + - [Step 2: Convert to MCAP](#step-2-convert-to-mcap) + - [Option 1: Your SLAM dataset is a directory of files.](#option-1-your-slam-dataset-is-a-directory-of-files) + - [Option 2: Your SLAM dataset is a ROS bag.](#option-2-your-slam-dataset-is-a-ros-bag) + - [Step 3: Visualize the Data](#step-3-visualize-the-data) +- [Deep Dive: Converting Multimodal Data to MCAP using Foxglove SDK](#deep-dive-converting-multimodal-data-to-mcap-using-foxglove-sdk) + - [Defining Message Schemas](#defining-message-schemas) + - [The Image Message](#the-image-message) + - [The IMU Message](#the-imu-message) +- [Where is the Drone? Enhance your Visualization with a URDF](#where-is-the-drone-enhance-your-visualization-with-a-urdf) + - [The Drone URDF](#the-drone-urdf) + - [The Launch File](#the-launch-file) + - [The Joint State Publisher](#the-joint-state-publisher) +- [Visualize the Data](#visualize-the-data) + + +## Step 1: Install Dependencies +A working ROS 2 installation is needed for this tutorial. We tested this pipeline using ROS 2 Humble with an Ubuntu 22.04 system. Run the following commands in a new terminal to get the SLAM and Foxglove dependencies: +```bash +sudo apt install \ + ros-$ROS_DISTRO-foxglove-bridge \ +    ros-$ROS_DISTRO-imu-tools \ + ros-$ROS_DISTRO-rtabmap-ros \ +    ros-$ROS_DISTRO-rosbag2-storage-mcap \ + ros-$ROS_DISTRO-image-proc +``` + +## Step 2: Convert to MCAP +The EuRocC MAV dataset standardized how SLAM data is collected. The EuRoC dataset contains IMU data represented as a .csv and an IMU configuration file, as well as side-by-side camera videos represented as timestamped images and camera configuration files. + +``` +imu0 +├── data.csv +└── sensor.yaml +cam +├── data +│   ├── .png +│   └── ... +├── data.csv +└── sensor.yaml +... +``` +Notice that there is no pointcloud or position estimates included in the original dataset. Luckily, Foxglove can be used to visualize data in real time using the [Foxglove SDK](https://foxglove.dev/blog/announcing-the-foxglove-sdk) for direct streaming or [Foxglove bridge](https://docs.foxglove.dev/docs/connecting-to-data/ros-foxglove-bridge) for visualizing ROS 1 or ROS 2 topics. In this tutorial, we will show how to use **both tools** in a ROS 2 workflow using the popular real-time SLAM package [RTAB-Map](https://introlab.github.io/rtabmap/). + +We will use the Foxglove SDK to convert the EuRoC dataset to an MCAP with the following topics to interact with RTAB-Map, +``` +/cam0/image_raw -> sensor_msgs/msg/Image +/cam1/image_raw -> sensor_msgs/msg/Image +/imu0 -> sensor_msgs/msg/Imu +``` +then record a new MCAP with pointcloud data and a visualization of our robot. MCAP is the default storage format for ROS 2 (Iron) and newer due to its optimized recording and ability to integrate with third-party tools outside ROS environments, making it the ideal format to work with SLAM data. If using a different SLAM dataset that is in ROS 1 .bag format or ROS 2 .db3 format, conversion to MCAP becomes trivial using the [MCAP command line interface (CLI)](https://mcap.dev/guides/cli). +#### Option 1: Your SLAM dataset is a directory of files. +Clone the [code repository](https://github.com/foxglove/tutorials/tree/main/datasets/EuRoC_MAV) for this tutorial. In a new python virtual environment, install the following dependencies: +```bash +pip install foxglove-sdk numpy opencv-python pyyaml +``` +Next, run our custom conversion script designed for the EuRoC dataset using the Foxglove SDK. We will break down how this script works in the [Deep Dive: Converting Multimodal Data to MCAP using Foxglove SDK](#deep-dive-converting-multimodal-data-to-mcap-using-foxglove-sdk) section of this tutorial so you can create your own conversion scripts. +```bash +python3 convert-euroc-2-mcap.py --src --dst .mcap +``` + +#### Option 2: Your SLAM dataset is a ROS bag. +The [MCAP CLI](https://mcap.dev/guides/cli) comes with commands to quickly convert bag files to MCAP! `mcap convert ` can be used as long as the message definitions contain the information that RTAB-Map is expecting. It may be beneficial to convert ROS 1 bags to ROS 2 bag format first before converting to MCAP to improve compatibility. Foxglove's built-in [debugging panels](https://docs.foxglove.dev/docs/visualization/panels/raw-messages) are a quick way to verify topic contents match. + +## Step 3: Visualize the Data +Just like that, we are ready to perform SLAM and visualize the data! Open four new terminals. In the first terminal, start the Foxglove bridge: +```bash +ros2 run foxglove_bridge foxglove_bridge +``` +In the second terminal, start an RTAB-Map instance with settings preset for EuRoC MAV datasets: +```bash +ros2 launch rtabmap_examples euroc_datasets.launch.py gt:=false +# Note: This example script accounts for camera and IMU calibrations and transformations. +# More calibration information is needed for other SLAM datasets. +``` + +In the third terminal, play back the MCAP file we made: +```bash +ros2 bag play --clock +``` +In the last terminal, record the resulting transformations and point clouds in a new MCAP file that can be visualized at a later time. +```bash +ros2 bag record -s mcap --all +``` +Finally, either watch the drone perform SLAM live by connecting to the [Foxglove Websocket](https://app.foxglove.dev) in your browser or import the new MCAP directly to Foxglove! + +![No Drone Image](media/no_drone_slam.png) + +# Deep Dive: Converting Multimodal Data to MCAP using Foxglove SDK +In this section, we will explore how the Foxglove SDK was used to create a custom MCAP conversion script that is compatible with ROS 2 listeners. Please refer to the [full script](https://github.com/foxglove/tutorials/tree/main/datasets/EuRoC_MAV/convert-euroc-2-mcap.py) script while following along. + +### Defining Message Schemas +We start by creating a new MCAP writer that will create an MCAP file for us to write to: +```python +writer = foxglove.open_mcap(out_mcap_path, allow_overwrite=True) # Open the mcap file for writing +``` + +In this tutorial, we will define our schemas to match the ROS 2 `sensor_msgs/msg/Image` and `sensor_msgs/msg/Imu` messages that RTAB-Map is expecting. + +```python +# Direct foxglove to our message definitions +imu_msg_path = Path("msgs/imu_flat.msg") +img_msg_path = Path("msgs/image_flat.msg") + +# Define our custom ROS 2 schemas +img_schema = Schema( +    name="sensor_msgs/msg/Image", +    encoding="ros2msg", +    data=img_msg_path.read_bytes(), +) +imu_schema = Schema( +    name="sensor_msgs/msg/Imu", +    encoding="ros2msg", +    data=imu_msg_path.read_bytes(), +) +``` + +The Foxglove SDK requires that ROS 2 messages be formatted in a delimited, concatenated format. This format is nearly captured using built-in ROS 2 tools such as `ros2 interface show sensor_msgs/msg/Image --no-comments`. More information about schema formatting is available [here](https://mcap.dev/spec/registry). For convenience, the `msgs` folder contains the formatted messages for the `sensor_msgs/msg/Image` and `sensor_msgs/msg/Imu` messages. + +Next, we make separate channels for each of the message schemas for convenient logging: +```python +# ros2msg channels require cdr encoding type +cam0_channel = Channel(topic="/cam0/image_raw", schema=img_schema, message_encoding="cdr") +cam1_channel = Channel(topic="/cam1/image_raw", schema=img_schema, message_encoding="cdr") +imu_channel = Channel(topic="/imu0", schema=imu_schema, message_encoding="cdr") +``` +### The Image Message +We start by looping through each image with `getImageMsg`, which takes in a timestamp and image and outputs an object of type `Image` +```python +def read_images(cam_directory, channel, cam_num): +    # Loop through the data.csv file and read in the image files +    with open(cam_directory + "/data.csv", "r") as csv_file: + reader = csv.reader(csv_file) +        next(reader)  # Skip the first row with headers +        for row in reader: + timestamp = int(row[0]) + image_name = row[1] + image_path = os.path.join(cam_directory, "data", image_name) +            if not os.path.exists(image_path): +                print(f"Image {image_path} does not exist") +                continue + +            # Convert image to ROS2 message and write to channel + image_msg = getImageMsg(image_path, timestamp, cam_num) + channel.log(serialize_message(image_msg), log_time=timestamp) +``` +The EuRoC dataset is composed of stereo images. For RGB images, the parameters of the `getImageMsg` function should be adjusted appropriately. +```python +def getImageMsg(img_path: str, timestamp: int, cam_num: int) -> Image: +    # Load as grayscale image data + img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE) +    if img is None: +        raise ValueError(f"Could not load image: {img_path}") +    + height, width = img.shape +    + sec = int(timestamp // 1e9) + nsec = int(timestamp % 1e9) + +    # Fill in the image message data + ros_image = Image() + ros_image.header = Header() + ros_image.header.stamp.sec = sec + ros_image.header.stamp.nanosec = nsec + ros_image.header.frame_id = "cam"+str(cam_num) + ros_image.height = height + ros_image.width = width + ros_image.encoding = "mono8" #Stereo images + ros_image.step = width  # For mono8, 1 byte per pixel + ros_image.data = img.tobytes() + +    return ros_image +``` + +### The IMU Message +The IMU data is saved in the data.csv file under the following format: +- Timestamp [ns], +- Angular velocity [rad s^-1] (x,y,z), +- Linear acceleration [rad s^-1] (x,y,z) + +The `sensor_msgs/msgs/Imu` message has the format of: +  - header (header) +  - orientation (quaternion) +  - orientation covariance (float32[9]) +  - angular velocity (vector3) +  - angular velocity covariance (float32[9]) +  - linear acceleration (vector3) +  - linear acceleration covariance (float32[9]) + +Notice that the orientation, orientation covariance, angular velocity covariance, and linear acceleration covariance are not present in the data for each timestamp. This is where the `gyroscope_noise_density` and `accelerometer_noise_density` parameters come into play in the `sensor.yaml` file. We can assume the diagonal of the covariance matrix to be a function of the IMU noise densities and sample rate. + +```python +def read_imu(imu_data_path, imu_channel, imu_yaml_path): +    # Get the IMU config with covariance information +    with open(imu_yaml_path, "r") as imu_yaml_file: + imu_yaml = yaml.load(imu_yaml_file, Loader=yaml.FullLoader) + +    # Get the noise and bias parameters, see https://github.com/ethz-asl/kalibr/wiki/IMU-Noise-Model for more details + sample_sqr_dt = np.sqrt(1.0/float(imu_yaml["rate_hz"])) + sigma_gd = imu_yaml["gyroscope_noise_density"]*sample_sqr_dt + sigma_ad = imu_yaml["accelerometer_noise_density"]*sample_sqr_dt + +    # Calculate the covariance matrices + angular_velocity_cov = np.diag([sigma_gd**2, sigma_gd**2, sigma_gd**2]).astype(np.float64) + linear_acceleration_cov = np.diag([sigma_ad**2, sigma_ad**2, sigma_ad**2]).astype(np.float64) +``` +We can now formulate the IMU ROS 2 message. Orientation is not measured by the IMU for this application, so we will leave its covariance empty. +```python + +    with open(imu_data_path, "r") as imu_file: + reader = csv.reader(imu_file) +        next(reader)  # Skip the first row with headers +        for row in reader: + timestamp = int(row[0]) + angular_velocity = [float(row[1]), float(row[2]), float(row[3])] + linear_acceleration = [float(row[4]), float(row[5]), float(row[6])] + + imu_msg = Imu() + imu_msg.header = Header() + imu_msg.header.stamp.sec = timestamp // int(1e9) + imu_msg.header.stamp.nanosec = timestamp % int(1e9) + imu_msg.header.frame_id = "imu4" # Transformation reference frame +            # Orientation + imu_msg.orientation = Quaternion() + imu_msg.orientation.x = 0.0 + imu_msg.orientation.y = 0.0 + imu_msg.orientation.z = 0.0 + imu_msg.orientation.w = 1.0 + orientation_cov = np.zeros((3,3), dtype=np.float64) + imu_msg.orientation_covariance = list(orientation_cov.flatten(order="C").astype(float)) +            # Angular velocity + imu_msg.angular_velocity = Vector3() + imu_msg.angular_velocity.x = angular_velocity[0] + imu_msg.angular_velocity.y = angular_velocity[1] + imu_msg.angular_velocity.z = angular_velocity[2] + imu_msg.angular_velocity_covariance = list(angular_velocity_cov.flatten(order="C").astype(float)) +            # Linear acceleration + imu_msg.linear_acceleration = Vector3() + imu_msg.linear_acceleration.x = linear_acceleration[0] + imu_msg.linear_acceleration.y = linear_acceleration[1] + imu_msg.linear_acceleration.z = linear_acceleration[2] + imu_msg.linear_acceleration_covariance = list(linear_acceleration_cov.flatten(order="C").astype(float)) + + imu_channel.log(serialize_message(imu_msg), log_time=timestamp) +``` +Now you know how to make custom schemas with the Foxglove SDK that can interface with ROS. The Foxglove SDK is not limited only to `Image` and `Imu` message types; in fact, there is a [wide selection of supported schemas](https://docs.foxglove.dev/docs/visualization/message-schemas) for every type of project. + +# Where is the Drone? Enhance your Visualization with a URDF +Adding a visualization of the drone is optional; however, adding one can lead to insights about correct transformations between the drone, cameras, and IMU. Since SLAM runs in real time, we will make a new [robot_state_publisher](https://docs.ros.org/en/humble/Tutorials/Intermediate/URDF/Using-URDF-with-Robot-State-Publisher-py.html) ROS 2 node that listens to RTAB-Map and dynamically updates the drone's pose. Please refer to [the LAFAN1 tutorial](https://foxglove.dev/blog/converting-the-lafan1-retargeting-dataset-to-mcap) to learn how to apply a URDF to an MCAP dataset in post-processing. + +### The Drone URDF +First, we will make a new ROS2 package to bundle our SLAM, robot_state_publisher, joint_state_publisher, and Foxglove bridge into one executable. +```bash +cd ros2_ws/src +ros2 pkg create --build-type ament_python --license Apache-2.0 euroc_slam +``` + +The EuRoC dataset was recorded on an Asctec Firefly drone, and its URDF model is included in the open-source [RotorS](https://github.com/ethz-asl/rotors_simulator) project for ROS 1. The exact URDF files and meshes for the Firefly can be downloaded [here](https://github.com/foxglove/tutorials/tree/main/datasets/EuRoC_MAV/ros2/src/euroc_slam). + +![drone_img](media/model.png) + +### The Launch File + +Navigate to the package directory and make a new launch file. Don't forget to [configure](https://docs.ros.org/en/humble/Tutorials/Intermediate/Launch/Launch-Main.html) `setup.py` to recognize launch, mesh, and urdf files! + +```bash +cd euroc_slam +mkdir launch +touch launch/firefly.launch.py +``` +Launch files are concise ways to bundle multiple ROS nodes together. `ros2 run foxglove_bridge foxglove_bridge` is equivalently represented in a launch file as: +```python +foxglove_bridge_node = Node( +    package='foxglove_bridge', +    executable='foxglove_bridge', +    name='foxglove_bridge', +    output='screen', +) +``` +In this script, we enable the following nodes: + +1. The Foxglove bridge to visualize ROS 2 topics. +2. The `robot_state_publisher` that publishes the URDF transformations and meshes. +3. A static transformation connecting the drone to the SLAM localization output. +4. A joint state publisher that simulates the rotors in motion. This step is purely for visual effect, as the motor torques are not included in the dataset's scope. +5. RTABMAP to perform SLAM in real time as our dataset is replayed. + +```python +from launch import LaunchDescription +from launch.actions import DeclareLaunchArgument, IncludeLaunchDescription, TimerAction +from launch.launch_description_sources import PythonLaunchDescriptionSource +from launch.substitutions import Command, LaunchConfiguration, PathJoinSubstitution +from launch_ros.actions import Node +from launch_ros.substitutions import FindPackageShare +from launch_ros.parameter_descriptions import ParameterValue + + +def generate_launch_description(): + use_sim_time = LaunchConfiguration('use_sim_time', default='false') +    +    # Generate URDF from xacro file (or read URDF file) + urdf_file = PathJoinSubstitution([FindPackageShare('rotors_description'), 'urdf', 'firefly.xacro']) + robot_description = ParameterValue(Command(['xacro ', urdf_file, ' namespace:=firefly']), value_type=str) + +    # Create nodes + foxglove_bridge_node = Node( +        package='foxglove_bridge', +        executable='foxglove_bridge', +        name='foxglove_bridge', +        output='screen', + ) + + robot_state_publisher_node = Node( +        package='robot_state_publisher', +        executable='robot_state_publisher', +        name='robot_state_publisher', +        output='screen', +        parameters=[{'use_sim_time': use_sim_time, 'robot_description': robot_description}] + ) + + static_transform_publisher_node = Node( +        package='tf2_ros', +        executable='static_transform_publisher', +        name='static_transform_publisher', +        output='screen', +        arguments=['0', '0', '0', '0', '0', '0', 'base_link', 'firefly/base_link'] + ) + + firefly_state_publisher_node = Node( +       package='rotors_description', +       executable='firefly_state_publisher', +       name='firefly_state_publisher', +       output='screen' + ) + + rtabmap_include = IncludeLaunchDescription( + PythonLaunchDescriptionSource([ + FindPackageShare('rtabmap_examples'), +            '/launch/euroc_datasets.launch.py' + ]), +        launch_arguments={ +            'gt': 'false' + }.items() + ) + +    return LaunchDescription([ + DeclareLaunchArgument( +            'use_sim_time', +            default_value='false', +            description='Use simulation (Gazebo) clock if true'), + foxglove_bridge_node, + TimerAction(period=2.0, actions=[robot_state_publisher_node]),  # 2 second delay + TimerAction(period=4.0, actions=[static_transform_publisher_node]),  # 4 second delay + TimerAction(period=6.0, actions=[rtabmap_include]), +        # TimerAction(period=10.0, actions=[firefly_state_publisher_node]) + ]) +``` +### The Joint State Publisher +The `firefly_state_publisher` is used to spin the rotors at a constant velocity during flight, defined by: +```python +self.increment = (360.0*self.spin_rate)/loop_rate +self.angle = ((self.angle + self.increment) % 360.0) - 180.0 +self.joint_state.position = [self.angle, -self.angle, self.angle, -self.angle, self.angle, -self.angle] +``` +This is purely visual and can be defined based on specific motor torque values, should they be available. + +## Visualize the Data +Open three terminals. In the first terminal, initialize the launch node containing RTAB-Map, the Foxglove bridge, and the URDF with: +```bash +ros2 launch euroc_slam firefly.launch.py +# Note: Don't forget to build and source your ROS environment after making changes! +``` +In the second terminal, play back the MCAP file we made: +```bash +ros2 bag play --clock +``` +In the last terminal, record the resulting transformations, point clouds, and URDF in a new MCAP file that can be visualized at a later time. +```bash +ros2 bag record -s mcap --all +``` +Open Foxglove and watch SLAM happen live, or load the generated MCAP file! + +![Finalviz](media/MH01_Final_gif_cut.gif) + +[Get started with Foxglove](https://app.foxglove.dev/human-interaction-and-robotics-lab/dashboard) and MCAP today! If you have any questions or need support, [join our community](https://discord.com/invite/vUVAdFmMFM)—we’d love to hear from you and help you succeed.