Rotations are non commutative in 3D
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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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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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We learn how to describe the 2D pose of an object by a 3×3 homogeneous transformation matrix which has a special structure. Try your hand at some online MATLAB problems. You’ll need to watch all the 2D “Spatial Maths” lessons to complete the problem set.
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We recap the important points from this lecture.
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When matching points between scenes with large different viewpoints we need to account for varying image size and rotation. SIFT features are a powerful way to achieve this.
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We summarise the important points from this lecture.
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We use MATLAB and some Toolbox functions to find corresponding points between two images using SURF features.
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We consider a robot, which has two rotary joints and an arm.
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We will learn how to create coordinate frames that have smoothly changing position and orientation over time.
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Now we introduce a variant of the Jacobian matrix that can relate our angular velocity vector back to our rates of change of the roll, pitch and yaw angles.
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A body moving in 3D space has a translational velocity and a rotational velocity. The combination is called spatial velocity and is described by a 6-element vector.