Converting depth map to pointcloud on Raspberry PI for realtime application
By calibrating your cameras you compute their interior orientation parameters (IOP - or intrinsic parameters). To compute the XYZ coordinates from the disparity you need also the exterior orientation parameters (EOP).
If you want your point cloud relative to the robot position, the EOP can be simplified, otherwise, you need to take into account the robot's position and rotation, which can be retrieved with a GNSS receiver and intertial measurement unit (IMU). Note that is very likely that such data need to be processed with a Kalman filter.
Then, assuming you got both (i) the IOP and EOP of your cameras, and (ii) the disparity map, you can generate the point cloud by intersection. There are several ways to accomplish this, I suggest using the collinearity equations.
I am developing a robot based on StereoPI. I have successfully calibrated the cameras and obtained a fairly accurate depth map. However, I am unable to convert my depth map to point cloud so that I can obtain the actual distance of an object. I have been trying to use cv2.reprojectImageTo3D, but see no success. May I ask if there is a tutorial or guide which teaches how to convert disparity map to point cloud? 
I am trying very hard to learn and find reliable sources but see on avail. So, Thank you very much in advance.