In a serial-link manipulator arm each joint has to support all the links between itself and the end of the robot. We introduce the recursive Newton-Euler algorithm which allows us to compute the joint torques given the robot joint positions, velocities and accelerations and the link inertial parameters.
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We start by considering the effect of gravity acting on a robot arm, and how the torque exerted will disturb the position of the robot controller leading to a steady state error. Then we discuss a number of strategies to reduce this error.
If your knowledge of dynamics is a bit rusty then let’s quickly revise the basics of second-order systems and the Laplace operator. Not rusty? Then go straight to the next section.
We summarise the important points from this lecture.
When it comes to describing a blob we can do more than just area, centroid position and bounding box. By looking at second order moments we can compute an ellipse that has the same moments of inertia as the blob, and we can use its aspect ratio and orientation to describe the shape and orientation […]
The linear algebra approach we’ve discussed is very well suited to MATLAB implementation. Let’s look at some toolbox functions that can simulate what cameras do. If you are using a more recent version of MVTB, ie. MVTB 4.x then please change>> cam.project(PW ‘Tcam’, transl(0.1, 0, 0)) to >> cam.project(PW ‘pose’, transl(0.1, 0, 0)).
For a binary image that contains multiple blobs we must first transform it using connectivity analysis or region labeling. Then we can describe each of the blobs in the scene we first need to transform the image using connectivity analysis. Each of the blobs can then be described in terms of its area, centroid position, […]
If we look at a binary image we can easily see distinct regions, that is, sets of pixels the same color as their neighbours. We call these blobs and they’re an important way of achieving an object rather than pixel view of the scene. We can describe these blobs by their area, centroid position, bounding […]
We can factorise the joint torque expression into an elegant matrix equation with terms that describe the effects of inertia, Coriolis and centripetal and gravity effects.
Let’s recap the important points from the topics we have covered about homogeneous coordinates, image formation, camera modeling and planar homographies.