Omnivision 🌐📸

A ros 2 package designed for 360° camera and lidar fusion. it captures equirectangular video feeds and lidar point clouds, fusing them to create textured 3d representations of the environment. omnivision provides visualization feeds and 360° depth information with only 2 sensors.

Applications include anywhere you need full surrounding depth information using only 2 sensors. This idea was originally created for full coverage lane detection, but would love to see other use cases!

This project was created for WayneHacks 3 @ Wayne State University! See the DevPost submission here.

Examples

Image Overlay

Texturized Pointcloud

Using depth information for plotting lanes

Features 🚀

• 360° Camera and LiDAR Integration: Full environmental coverage from 3D LiDAR and 360° camera.

• Data Fusion: Combine camera and LiDAR data to generate textured point clouds.

• Depth Map Generation: Creates textured and grayscale depth maps.

• Dynamic Visualization Compute: Only generates pointclouds / depthmaps when topics have subscribers.

Installation 🛠️

Prerequisites:w

• ROS 2 (Humble or newer recommended)

• Python 3.8+

• OpenCV

• PCL

• NumPy

Steps

• Clone the repository into your ROS 2 workspace:

git clone git@github.com:BlaineKTMO/omnivision.git /path/to/ros2_ws/src/omnivision

Install dependencies:

sudo apt install ros-<your_ros2_distro>-cv-bridge ros-<your_ros2_distro>-pcl-ros
pip install numpy opencv-python

Build the package:

cd /path/to/ros2_ws
colcon build --symlink-install

Source the workspace:

source /path/to/ros2_ws/install/setup.bash

Usage 🖥️

Launching the Package

To start the Omnivision system, use the provided launch file:

ros2 launch omnivision bringup.launch.py

Parameters

Customize the launch file with the following parameters:

• camera_topic: Topic name for the 360-degree camera feed (default: /camera/image_raw).

• lidar_topic: Topic name for the LiDAR point cloud data (default: /lidar/points).

• output_topic: Topic name for the fused textured point cloud (default: /omnivision/fused_cloud).

• depth_map_topic: Topic name for the generated depth map (default: /omnivision/depth_map).

Example

To launch with custom topics:

ros2 launch omnivision bringup.launch.py camera_topic:=/my_camera lidar_topic:=/my_lidar

To Do (Contributions Welcome!) 🛠️

• Optimization: Improve processing efficiency and reduce resource usage.

• LiDAR Interpolation: Add an option to interpolate LiDAR data for denser point clouds.

• Launch File Configuration: Expand the launch file to support more customization options.

• Documentation: Add additional details for usage or debugging.

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