Automated rapid mapping of joint orientations with mobile LiDAR

This paper introduces three-dimensional axis mapping (3DAM), a new method for joint orientation estimation that rapidly collects data from a mobile platform containing a scannerless LiDAR and an inertial measurement unit (IMU). The mobile platform is moved through the environment either as a handheld device or by mounting it to a remotely operated or robotic vehicle. 3DAM is formulated as a global state estimation problem that estimates the orientation of the mobile platform and the joint set orientations by minimizing the uncertainty introduced by the inherently noisy sensors. This requires a dual-parameterization of both the orientation of joint sets and the mobile platform to permit the use of state estimation techniques. 3DAM was field tested in three separate locations and is directly compared to hand measurements and stationary LiDAR. In all experiments, it is shown that 3DAM produces stereonets comparable to other methods, yet does so with lower-cost hardware and significantly reduced effort.