In our SLAM algorithm, we want to rotate GPS co-ordinates to SLAM co-ordinate system so that those GPS positions can be used for bundle adjustment in monocular SLAM (Scale correction).
We have used following procedure for rotation.
Convert Lat, Long, Att GPS co-ordinates to XYZ co-ordinate using Geoconverter library. (Resetting origin same as SLAM co-ordinate's origin)
Therefore, calculate rotation matrix between XYZ GPS co-ordinates and SLAM co-ordinates using rodrigues rotation formula for the first vector after origin.
Then, for each XYZ GPS position use the rotation matrix to calculate the GPS co-ordinates in SLAM co-ordinate system.
However, the results are not as expected, the GPS co-ordinate plane does not align with SLAM co-ordinates, hence bundle adjustment fails.
To check the actual position of the GPS co-ordinates after rotation, we plotted them (as shown below).
Front view (GPS(olive), SLAM(blue), MapPoints(black))
Without MapPoints
Side view to understand GPS and SLAM are in different plane
Side view with MapPoints
Side view different angle
Can you point out the mistake in the process or suggest an alternate process to align GPS data.
Thanks
Saurabh Kumar
Related
I have a camera at a known fixed location and orientation.
I also have a plane at a known location whose z position changes.
I want to turn the image from the camera into a top down view of the plane.
I can do this without knowing any positions by using the 4 points of the plane for a homography matrix and warping the image but each time the plane moves in Z I have to repeat this process.
After searching around online most methods seem to center on finding features of the image (using SIFT or something like it) then computing a homography matrix.
With the problem so constrained I thought there may be a simple linear algebra based approach.
Considering the camera is not tilted, it is easy to get the distance. However, can you refer a source where camera is tilted at some angle on y axis. By tilt i mean pitch. Also the camera is not looking directly at the object.
In the pinhole camera model, is it possible to determine the rotation required from the optical/principal axis (the axis which pierces the image plane) to intersect a given pixel coordinate (u,v)?
I have an image where I am detecting a marker in space, and have the intrinsic and extrinsic camera parameters available. I am using the extrinsic parameters to cast a 2d ray into a separately constructed map (which is overhead and 2d), however I would like the ray angle to change depending on if the detected marker is to the left or right inside of the image.
My first thought was to use arctan utilizing the focal length and the u coordinate (x-axis on image plane from center of image) to determine an angle, however I don't think the units of measurement cooperate: one should be in real world meters and the other is arbitrary pixels.
below you can see the result of the optical flow if a camera makes a translation movement. If the camera makes a roll rotation the result looks like the second picture. Is it possible to retrieve the yaw angle from a camera if its only rotation around the yaw axis?
I think in the optical flow you can recognize if the camera is rotating around the yaw axis (z-axis), but i don't know how to retrieve the information how much the cam has rotated.
I would be gradeful for any hints. Thanks
Translation:
Roll rotation:
Orientation of camera:
If you have a pure rotation of your cam then you can use findhomography. You need four point correspondence in your pictures. For a pure rotation the homography matrix is already a rotation matrix. Otherwise you need to decompose the homograohy matrix. For a camera movement off 6 dof you can use the function find essential matrix and decompose this to translation and rotation.
I have a robot and a camera. The robot is just a 3D printer where I changed the extruder for a tool, so it doesn't print but it moves every axis independently. The bed is transparent, and below the bed there is a camera, the camera never moves. It is just a normal webcam (playstation eye).
I want to calibrate the robot and the camera, so that when I click on a pixel on a image provided by the camera, the robot will go there. I know I can measure the translation and the rotation between the two frames, but that will probably return lots of errors.
So that's my question, how can I relate the camera and a robot. The camera is already calibrated using chessboards.
In order to make everything easier, the Z-axis can be ignored. So the calibration will be over X and Y.
It depends of what error is acceptable for you.
We have similar setup where we have camera which looks at some plane with object on it that can be moved.
We assume that the image and plane are parallel.
First lets calculate the rotation. Put the tool in such position that you see it on the center of the image, move it on one axis select the point on the image that is corresponding to tool position.
Those two points will give you a vector in the image coordinate system.
The angle between this vector and original image axis will give the rotation.
The scale may be calculated in the similar way, knowing the vector length (in pixels) and the distance between the tool positions(in mm or cm) will give you the scale factor between the image and real world axis.
If this method won't provide enough accuracy you may calibrate the camera for distortion and relative position to the plane using computer vision techniques. Which is more complicated.
See the following links
http://opencv.willowgarage.com/documentation/camera_calibration_and_3d_reconstruction.html
http://dasl.mem.drexel.edu/~noahKuntz/openCVTut10.html