The most common type of actuator is a rotary electric motor so let’s look at the basic principles.
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We use MATLAB and some Toolbox functions to create a robot controller that moves a camera so the image matches what we want it to look like. We call this an image-based visual servoing system.
Let’s recap the important points from the topics we have covered in our discussion of optical flow and visual servoing.
Actuators are the components that actually move the robot’s joint. So let’s look at a few different actuation technologies that are used in robots.
Visual servoing is concerned with the motion of points in the world. How can we reliably detect such points using computer vision techniques.
There is a lot of information in an image which we need to summarize somehow. An intensity histogram is one form of summary that provides useful information about how well the exposure of our camera is adjusted.
It is common to think about an assembly task being specified in terms of coordinates in the 3D world. An alternative approach is to consider the task in terms of the relative position of objects in one or more views of the task — visual servoing.
We recap the important points from this masterclass.
So far we have worked out the torques on a robot’s joints based on joint position, velocity and acceleration. For simulation we want the opposite, to know its motion given the torques applied to the joints. This is called the forward dynamics problem.
We describe the velocity coupling terms of the robot as a matrix which represents how the torque on one joint depends on the velocity of other joints.