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A robot joint controller is a type of feedback control system which is an old and well understood technique. We will learn how to assemble the various mechatronic components such as motors, gearboxes, sensors, electronics and embedded computing in a feedback configuration to implement a robot joint controller.

The orientation of a body in 3D can also be described by two vectors, often called the approach and orientation vectors.

A robot joint is a mechatronic system comprising motors, sensors, electronics and embedded computing that implements a feedback control system.

Let’s look at some simple monadic functions such as type conversion, brightness and contrast adjustment, inversion and posterisation and the effect they have on an image.

We recap the important points from this masterclass.

We consider a robot with three joints that moves its end-effector on a plane.

We learn how to describe the orientation of an object by a 2×2 rotation matrix which has some special properties. Try your hand at some online MATLAB problems. You’ll need to watch all the 2D “Spatial Maths” lessons to complete the problem set.

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 revisit the simple 2-link planar robot and determine the inverse kinematic function using simple geometry and trigonometry.

A number of strategies exist to reduce the effect of these coupling torques between the joints, from introducing a gearbox between the motor and the joint, to advanced feedforward strategies.