Lidar Sensor Integrators IMU GPS RTK

The objective of this project is to generate an algorithm (to be run on a mini pc) to create a cloud of data points obtained from 3 systems: LIDAR, GPS RTK and IMU. For this the following aspects must be taken into account: Relatives coordinates When it comes to the point cloud map creation, we need to know exact position of each scanned point in the final coordinate system bounded to a local ground. To this point, we were only able to acquire coordinates relatively to a LiDAR’s position. Using an integration of an IMU and a GPS module. Interpolation Let’s assume that the communication lines have a negligible traffic delay and the processor of the on-board computer receives the data values almost immediately after they were measured by the sensors. The principle is the same for each of the three devices. Right after the data is read from the line by a dedicated method, the computer’s current system time is assigned to the record. The record is then stored into a data buffer. Each sensor has its own buffer and a thread managing the sensor’s services. .We take a LiDAR’s point from its buffer. .We take first two IMU’s records from its buffer. .If the LiDARs point time stamp is lower number than the time stamp of the first IMU record, the point is discarded. This repeats until the point’s time stamp is greater than the first IMU record’s time stamp. .When the point’s time stamp lies between the two time stamps from IMU records, the two IMU records are used for the point’s transformation. .If the point’s time value is greater than the second IMU record’s time, the first IMU record is discarded, the second takes place as the first and the second place is filled with a new record from the buffer. We described the principle on IMU records but the same applies to the GPS records in parallel. Make coordinates systems transformations Calculated point cloud with raw sensors records This approach stores raw data from each sensor separately resulting in three binary files as an output from the vehicle after a survey. A point cloud from it is calculated on a PC and allows for better debugging. It also gives us the possibility to generate models with various parameters from one data set. If we detect some major problem in the data set, it can be fixed. Offline conversion to LAS Standard Correction Imprecision and Uncertainty Problems