  Environment perception is a key component of any autonomous system and is
often based on a heterogeneous set of sensors and fusion thereof for which
sensor sensor calibration plays fundamental role. It can be divided to
intrinsic and extrinsic sensor calibration. Former seeks for internal
parameters of each individual sensor, while latter provides coordinate frame
transformation between sensors. Calibration techniques require correspondence
registration in the measurements which is one of the main challenges in the
extrinsic calibration of heterogeneous sensors, since generally, each sensor
can operate on a different physical principle. Measurement correspondences can
originate from a designated calibration target or from features in the
environment. Additionally, environment features can be used to estimate motion
of individual sensors and the calibration is found by aligning these estimates.
Motion-based calibration is the most common approach in the online calibration
since it is more practical than the target-based methods, although it can lack
in accuracy. Furthermore, online calibration is beneficial for system
robustness as it can detect and adjust recalibration of the system in runtime,
which can be seen as a prerequisite for long-term autonomy.
