Calibration and Sensor Fusion
Most modern autonomous systems in applications such as manufacturing, transportation, and construction, employ multiple sensors. Sensor Fusion is the process of bringing together data from multiple sensors, such as radar sensors, lidar sensors, and cameras. The fused data enables greater accuracy because it leverages the strengths of each sensor to overcome the limitations of the others.
To understand and correlate the data from individual sensors, you must develop a geometric correspondence between them. Calibration is the process of developing this correspondence. Use Lidar Toolbox™ functions to perform lidar-camera calibration. To get started, see What Is Lidar-Camera Calibration?
Lidar Toolbox also supports downstream workflows such as projecting lidar points on images, fusing color information in lidar point clouds, and transferring bounding boxes from camera data to lidar data.
|Lidar Camera Calibrator
|Interactively establish correspondences between lidar sensor and camera to fuse sensor data (Since R2021a)
Detect Calibration Parameters
Calibrate Lidar and Camera
Fuse Sensor Data
|Project lidar point cloud data onto image coordinate frame (Since R2020b)
|Fuse image information to lidar point cloud (Since R2020b)
|Estimate 3-D bounding boxes in point cloud from 2-D bounding boxes in image (Since R2020b)
|Estimate 2-D bounding box in camera frame using 3-D bounding box in lidar frame (Since R2021a)
- What Is Lidar-Camera Calibration?
Fuse lidar and camera data.
- Calibration Guidelines
Guidelines to help you achieve accurate results for lidar-camera calibration.
- Coordinate Systems in Lidar Toolbox
Overview of coordinate systems in Lidar Toolbox.
- Get Started with Lidar Camera Calibrator
Interactively calibrate lidar and camera sensors.
- Read Lidar and Camera Data from Rosbag File
This example shows how to read and save images and point cloud data from a rosbag file.