#### Describing rotation and translation in 3D

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We learn how to describe the 3D pose of an object by a 4×4 homogeneous transformation matrix which has a special structure.

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We learn how to describe the 3D pose of an object by a 4×4 homogeneous transformation matrix which has a special structure.

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The orientation of a body in 3D can also be described by a unit-Quaternion, an unusual but very useful mathematical object. In the MATLAB example starting at 3:48 I use the Quaternion class. For Toolbox version 10 (2017) please use UnitQuaternion instead.

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The orientation of a body in 3D can also be described by a single rotation about a particular axis in space.

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The orientation of a body in 3D can be described by three angles, examples of which are Euler angles and roll-pitch-yaw angles. Note that in the MATLAB example at 8:24 note that recent versions of the Robotics Toolbox (9.11, 10.x) give a different result: >> rpy2r(0.1,0.2,0.3)ans = 0.9363 -0.2751 0.2184 0.2896 0.9564 -0.0370 -0.1987 0.0978 […]

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If we apply a sequence of 3D rotations to an objects we see that the order in which they are applied affects the final result.

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This is an exercise in which you can build a 3D coordinate frame by printing, cutting, folding and stapling.

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We revisit the fundamentals of 3D geometry that you would have learned at school: coordinate frames, points and vectors.

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In order to determine the size and distance of objects in the scene our brain uses a number of highly evolved tricks. Let’s look at some of these.

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We revisit the important points from this masterclass.

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We combine what we’ve learnt about smoothly varying position and orientation to create smoothly varying pose, often called Cartesian interpolation.