We consider a robot with four joints that moves its end-effector in 3D space.
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We learn how to create smoothly varying orientation in 3D by interpolating Euler angles and Quaternions. In the MATLAB example starting at 5:44 I use the Quaternion class. For Toolbox version 10 (2017) please use UnitQuaternion instead.
We learn how to describe the 3D pose of an object by a 4×4 homogeneous transformation matrix which has a special structure.
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.
The orientation of a body in 3D can also be described by a single rotation about a particular axis in space.
The orientation of a body in 3D can also be described by two vectors, often called the approach and orientation vectors.
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 […]
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.
This is an exercise in which you can build a 3D coordinate frame by printing, cutting, folding and stapling.
We recap the important points from this lecture.