7

The following diagram (1) illustrates a method by which a Lancaster navigator determined airplane height above the water of a lake. Such a method is useful if the ground lacks features needed for other forms of Visual Servoing. A program I saw about mission Chastise showed one spotlight shining green and the other red, to avoid confusion about which way to ...


6

Using a so-called optical flow sensor is the best way to help with holding the horizontal (i.e. in X-Y plane) position. I don't see any reason why you couldn't do the same for vertical control, although a sonar is probably easier and cheaper to use for this (likewise, if you are indoors, you could use 2 sonars for the horizontal position as well) People ...


4

So it sounds like you have an external camera system to track the end effector position and orientation? In that case I would use QR codes or april tags. Stick a couple of these on your end effector, and make sure that you put enough of them that 1 is always visible from your camera. The apriltags library provides the ability to extract position and ...


3

It happens many times that set-points fed in our systems do change in a step-wise manner. Your intuition of filtering those variations is correct and represents a common practice. Here I'd give two cases: You have direct access to $\dot{s}$, which is thus your velocity reference varying step-wise. Then, you could consider a simple frequency based filter, ...


2

I think you took a wrong turn in your approach. I know at all the time the position (a) of the end tool by the T_base^tool - matrix, and from the image analysis i know the position (b) of the object relative to the camera frame for which i compute the difference as such c = b - a. You don't care about position (a). You care about the position in the ...


2

We need to be able to track 3 points, (sometimes called features), on a solid body to estimate its 6dof pose relative to the camera. Each has an estimated position in the 2D camera image. If you imagine having only two points visible on the object, you can rotate the object around the line (axis) joining the two points and the 2D position in the image ...


1

The problem in both cases is to move the robot tool to some pose relative to an object. Let's assume the camera is attached to the end of a robot arm (eye in hand case) so we will consider this a problem in moving the camera. The tool will always be at a fixed relative pose to the camera. In PBVS we uses a geometric model of the object, plus known camera ...


1

You can definitely use Visual Servoing for pose maintenance in the X-Y plane. You need to have sufficient distinct features on the ground to get a good estimate of drift/spin etc. For example, on an uniform and large ground/field, lack of features might become a problem. But things will be more in your control and you can add visual cues into the scene to ...


1

Generally, visual servoing is a way to measure your position relative to features that are seen on the camera, without having to know your absolute position. In other words, registering those features with those in a global frame would be a separate process. Remember that visual servoing is not limited to simply providing more data about your static ...


1

Because a camera is a range-only sensor, you cannot directly estimate the relative position of the object. Additionally, because you have only one object, there are infinite solutions that are equally possible, given only the angular camera measurements. Possible solutions: If you have two images with a known relative position between the two, then you can ...


1

It's odd that you're suggesting computing the position of a landmark. Literally, a mark on the land -- a position that you should already know and will use to localize your vehicle. You can give it whatever arbitrary location you want. If you have only one landmark, the most logical choice for it is [0, 0, 0]. Or, you could determine the X,Y coordinates ...


1

The visual servoing will probably be sufficient for keeping the open end of the tube in view -- keeping the proper orientation of the vehicle with respect to the tube. The goal will be to keep the center of the detected circle in the center of the camera's view. However, this technique will not be sufficient to tell you how far you are from the edges of ...


1

If you cannot sense your closeness to the wall of the cylinder, then the image itself will have to guide you. When the end of the cylinder is completely within the field of view of the camera, I think your approach is good. When the circle becomes an ellipse that means the focal plane of the camera is skewed relative to the end of the pipe, and you will ...


1

For a 6 degree of freedom manipulator there are an infinite number of (positions + orientations) which will keep a point object centered in the frame. When you determine the position of the object relative to the camera frame, is it allowable to ignore orientation changes and move the camera (keeping its current orientation) to track the object? Or ...


1

Image features are connected to the camera pose through two steps: (1) the relationship between the feature pixel coordinates and its homogeneous coordinates in the camera reference frame, and (2) the relationship between the camera reference frame and the world frame. Take a look at this figure, where the world frame is denoted with subscript 0 and the ...


1

You are using a target set of image points that are impossible to achieve. Simply shifting two of the points in one direction within image coordinates does not correspond to a rigid transformation of your 3D set of points. It may make sense for orthographic projections in CAD software, but cameras have perspective so you need to include that in your ...


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