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Let’s recap the important points from the topics we have covered about light, wavelength, spectrums, light sources, reflection, reflectance functions, cone cells, tristimulus and chromaticity space.

As the illumination level changes so do the red, green and blue tristimulus values, but they are linearly related. We can separate brightness from chromaticity which is a two dimensional representation of color. We discuss briefly the effect of gamma encoding on the color reproduction process.

Humans are trichromats which means that our eyes have three types of cone cells which are sensitive to different parts of the spectrum: red, green and blue light. They perform a non-unique mapping from an arbitrary spectrum of light into three signals which are known as a tristimulus which we perceive as a particular color. […]

We can create most colors by a suitable mixture of three primary colored light sources, typically red, green and blue. Let’s look at how color mixing works.

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.

A more efficient trajectory has a trapezoidal velocity profile.

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)).

Light entering our eyes stimulates the photoreceptor cells in the retina of our eye: color sensitive cone cells that we use in normal lighting conditions and monochromatic rod cells we use in low light. The density of these cells varies across the retina, it is high in the fovea, low in the peripheral vision region […]

We summarise the important points from this lecture.

We learn to compute a trajectory that involves simultaneous smooth motion of many robot joints.