Kalibr is a toolbox dedicated to solving a range of calibration problems, including multi-camera calibration, visual-inertial calibration (CAM-IMU), multi-inertial calibration (IMU-IMU), and rolling shutter camera calibration. It focuses on determining the intrinsic and extrinsic parameters of sensors within a system. The toolbox supports a wide array of camera models and allows for the calibration of IMUs with respect to base inertial sensors or cameras. Kalibr primarily uses optimization-based approaches to achieve accurate sensor pose and parameter estimation.
Kalibr uniquely supports a broad spectrum of calibration scenarios, from simple multi-camera setups to complex visual-inertial and multi-IMU systems. The toolbox offers flexible configuration options, including support for various camera models and IMU types. Its active development and integration with ROS make it suitable for robotics and computer vision applications. The extensive documentation and community support further enhance its usability.
- Multi-Camera Calibration: Enables precise calibration of camera systems with non-globally shared views.
- Visual-Inertial Calibration: Allows calibration of camera-IMU systems for accurate pose estimation.
- Multi-Inertial Calibration: Facilitates calibration of multiple IMUs relative to each other or to a base inertial sensor.
- Rolling Shutter Camera Calibration: Provides full calibration for cameras exhibiting rolling shutter effects.
- ROS Integration: Offers seamless integration with the Robot Operating System (ROS) for easy use in robotic applications.
- Extensive Documentation: Includes detailed documentation and tutorials for various calibration scenarios.
- Active Development: Under continuous development with regular updates and bug fixes.
Kalibr is a mature and actively maintained toolbox with a strong track record of use in research and industry. It has a substantial number of stars and forks on GitHub, indicating community engagement. Recent commits and issue activity suggest ongoing development and support. The comprehensive documentation and a dedicated community further solidify its reliability. Numerous publications cite Kalibr, underscoring its impact.
Kalibr benefits robotics researchers and developers needing accurate sensor pose and intrinsic parameters for applications like SLAM, visual odometry, and robot navigation. It provides a robust and versatile solution for calibrating various sensor setups, offering a significant advantage compared to manual calibration methods or less comprehensive tools. By enabling precise sensor data, Kalibr improves the accuracy and reliability of robotic systems.