  This work presents a novel target-free extrinsic calibration algorithm for a
3D Lidar and an IMU pair using an Extended Kalman Filter (EKF) which exploits
the \textit{motion based calibration constraint} for state update. The steps
include, data collection by motion excitation of the Lidar Inertial Sensor
suite along all degrees of freedom, determination of the inter sensor rotation
by using rotational component of the aforementioned \textit{motion based
calibration constraint} in a least squares optimization framework, and finally,
the determination of inter sensor translation using the \textit{motion based
calibration constraint} for state update in an Extended Kalman Filter (EKF)
framework. We experimentally validate our method using data collected in our
lab and open-source (https://github.com/unmannedlab/imu_lidar_calibration) our
contribution for the robotics research community.
