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Robotic Motion The linear algebra of Canadarm

Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

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Page 1: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

Robotic Motion

The linear algebra of Canadarm

Page 2: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

The robot arm simulation

The movements of the robotic arm can be described using orthogonal matrices.

Page 3: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

Six degrees of freedom

The first segment is fixed to the wall but is free to rotate. The motion of the 2nd segment is confined to a plane;

however, combining it with the rotation of the 1st segment allows it to move in the right half-space.

The third segment can rotate and move in a plane and the same is true of the fourth segment.

Page 4: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

Spherical co-ordinates We want to determine this

in the Cartesian co-ordinate system.

Note that z/r= cos φ. x/s= cos θ and y/s= sin θ. To eliminate s, we note

s/r = sin φ. Therefore x=r sin φ cos θ,

y= r sin φ sin θ, z= r cos φ.

Thus if r=1, the direction of the vector is given by two co-ordinates, φ and θ.

We can reverse the calculation: given x, y,z, what are the values of r, θ, and φ ?

s

(x,y,z)

Page 5: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

Inverse Kinematics

To move the robotic arm to the position (x,y), we need to rotate the first arm by an angle α and the second arm by β.

We will assume known the lengths L1 and L2 of the two arms.

(x,y)

Page 6: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

Law of sines

The angle α is the sum of two angles: arctan(y/x) and the angle φ which we can calculate using the sine law.

φφ =

Page 7: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

Law of cosines

This is a generalization of the Pythagorean theorem.

We will apply this to the robotic problem.

Page 8: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

Calculation α and β

The second term coming from the angle (x,y) makes with the horizontal axis.

Page 9: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

Six degrees of freedom again

P is specified using three co-ordinates and is obtained from the three rotations 1, 2 and 3 indicated.

Rotations 4 and 5 are used to orient the axis of the claw.

Rotation 6 rotates the claw to the desired angle about its axis.

Page 10: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

Moving a solid in a plane

It requires two co-ordinates (x,y) to specify the position of A after it is moved.

One more parameter, the angle α, is needed to specify the rotation with respect to the horizontal axis AB.

A B

(x,y)

Page 11: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

Robotic motion and orthogonal matrices Any rotation in R2 is

given by a matrix of this form.

These matrices are orthogonal: AAt = I.

We have shown all 2 x 2 orthogonal matrices A with det A=1 have this form.

The motion of a robotic arm in R3 is a sequence of translations and rotations.

With a suitable basis, any rotation in R3 is of the following form:

Page 12: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

The cross product

Here n is a vector of unit length perpendicular to both the vectors a and b.

Page 13: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

The right hand rule The green vector

depicting the cross product changes as the angle between the two vectors changes.

The cross product is neither commutative nor associative but satisfies the Jacobi identity.

a, b, c in R3

Page 14: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

Transformations of R3 preserving lengths and angles Theorem: Any movement of a solid in space

is the composition of a translation and rotation about some axis. After an appropriate choice of basis for R3, the rotation is given by the matrix:

Page 15: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

Rotations in Rn

Any orthogonal matrix has determinant +1 or -1.

Page 16: Robotic Motion The linear algebra of Canadarm. The robot arm simulation The movements of the robotic arm can be described using orthogonal matrices

Rotations in Rn with det = -1.

This has the following geometric meaning: