MEAM 520. More Velocity Kinematics

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MEAM 520 More Velocity Kinematics Katherine J. Kuchenbecker, Ph.D. General Robotics, Automation, Sensing, and Perception Lab (GRASP) MEAM Department, SEAS, University of Pennsylvania Lecture 12: October 18, 2012

Project 1 : PUMA Light Painting

RUNNING THE PUMA The basic work flow when using the PUMA 260 arm is 1. Make sure the Emergency Stop (E-stop) button is engaged (pressed down). 2. Call!"#$%&$'&()*$'+,$'-)./)01)./)2-3$4)./567, where the number following delay is the minimum allowable time, in milliseconds, between calls to!"#$%-'80. This may be set to any value above 0.5ms. This will display a warning that the PUMA will return to the home position. Ensure that the workspace is clear and manually move the PUMA closer to the home position if you think it may hit the table or an object. 3. Type 'y' or 'yes' then hit Enter to continue. 4. Release the E-stop by pulling up on the button, at which time the PUMA will return to the home position. 5. In a separate MATLAB process, call 9&$'&:'$#-;"<<-' to begin capturing video from the webcam. 6. Make a light painting, using!"#$%-'80 to command the robot to move. Remember to call!"#$=>2?1 to enable the LED and use!"#$=>2%-& to select the color. 7. Call 9&0!:'$#-;"<<-' to finish capturing video. 8. Return the PUMA to the home position, if possible. 9. Call!"#$%&0! to disable the controller. 10. Engage the E-stop by pressing the button down. 11. Use #$@-AB+-0C1+D#$E- to create long-exposure picture and video. Optionally, you may wish to save the image files to a different location using 9$8-D#$E-9F0:03+-' before starting a new video. There are several other things to keep in mind: Do NOT use the G3-$'/$33 command once the PUMA has been initialized before calling!"#$%&0!, otherwise MATLAB will crash. Test the video capture before running your whole light painting.

Confirmed Midterm Date Thursday, November 8, in class ~ email KJK if you have a severe conflict ~

Velocity Kinematics Slides created by Jonathan Fiene

How do the velocities of the joints affect the linear and angular velocity of the end-effector? These quantities are related by the Jacobian, a matrix that generalizes the notion of an ordinary derivative of a scalar function. Jacobians are useful for planning and executing smooth trajectories, determining singular configurations, executing coordinated anthropomorphic motion, deriving dynamic equations of motion, and transforming forces and torques from the end-effector to the manipulator joints.

The Manipulator Jacobian explore how changes in joint values affect the end-effector movement could have N joints, but only six end-effector velocity terms (xyzpts) The Jacobian matrix lets us calculate how joint velocities translate into end-effector velocities (depends on configuration) look at it in two parts - position and orientation How do we calculate the position Jacobian?

ṗ = J p (q) q endpoint velocity joint velocity Jacobian matrix J p = δx δq 1 δy δq 1 δz δq 1 δx... δx δq 2 δq n δy δq 2... δy δq n δz... δz δq 2 δq n Prismatic Revolute

A Use for the Position Jacobian What joint velocities should I choose to cause a desired end-effector velocity? (inverse velocity kinematics) This works only when the Jacobian is square and invertible (non-singular). SHV 4.11 explains what to do when the Jacobian is not square: rank test (v is in range of J) use J + (right pseudoinverse of J) when the robot has extra joints, there are many solutions

Singularities Singularities are points in the configuration space where infinitesimal motion in a certain direction is not possible and the manipulator loses one or more degrees of freedom Mathematically, singularities exist at any point in the workspace where the Jacobian matrix loses rank. a matrix is singular if and only if its determinant is zero: det(j) =0

Position Singularities : Planar RR d 0 2 = a 2c 12 + a 1 c 1 a 2 s 12 + a 1 s 1 0 (x, y) J = [ ] a1 s 1 a 2 s 12 a 2 s 12 a 1 c 1 + a 2 c 12 a 2 c 12 a 2 θ 2 a 1 θ 1

Position Singularities : Planar RR For θ 2 =0 The Jacobian collapses to have linearly dependent rows [ ] a1 s J θ2 =0 = 1 a 2 s 1 a 2 s 1 a 1 c 1 + a 2 c 1 a 2 c 1 a 2 (x, y) This means that actuating either joint causes motion in the same direction a 1 θ 2 θ 1

Questions?

The Manipulator Jacobian explore how changes in joint values affect the end-effector movement could have N joints, but only six end-effector velocity terms (xyzpts) The Jacobian matrix lets us calculate how joint velocities translate into end-effector velocities (depends on configuration) look at it in two parts - position and orientation How do we calculate the orientation Jacobian?

And now, angular velocity ω = J ω (q) q final frame angular velocity joint velocities

A Note about Notation ω k i,j this is the angular velocity of frame j with respect to frame i, expressed in frame k SHV 4.1 gives a good explanation of angular velocity for fixed-axis rotation. SHV 4.2-4.5 go into greater detail.

The Angular Velocity of Connected Rigid Bodies ω 0 0,1 =0ˆx 0 +0ŷ 0 + θ 1 ẑ 0 ω 1 1,2 =0ˆx 1 +0ŷ 1 + θ 2 ẑ 1 θ 2 ω 0 1,2 = R 0 1 ω 1 1,2 θ 1 ω 0 0,2 = ω 0 0,1 + R 0 1 ω 1 1,2 =0ˆx 0 +0ŷ 0 +( θ 1 + θ 2 )ẑ 0 ω 0 0,n = n i=1 R 0 i 1 ω i 1 i 1,i ω 0 0,n = n (R 0 i 1ẑ) θ i i=1 note: this holds for revolute joints only (by definition, a prismatic joint cannot create angular velocity)

And now, for that Jacobian! ω 0 0,n = n i=1 ρ i (R 0 i 1ẑ) θ i 0 for prismatic ρ i = 1 for revolute θ 1 ω 0 0,n = ρ 1 ẑ ρ 2 R 0 1ẑ ρ 2R 0 2ẑ... ρ nr 0 n 1ẑ θ 2... θ n ω = J ω (q) q

Jp (3 x n) cartesian velocity Jacobian J = J ω (6 x n) Jacobian a.k.a. manipulator Jacobian a.k.a. geometric Jacobian (3 x n) angular velocity Jacobian The Jacobian is easily constructed from the manipulator s forward kinematics. What do you need from the forward kinematics?

Revisiting Singularities Singularities are points in the configuration space where infinitesimal motion in a certain direction is not possible and the manipulator loses one or more degrees of freedom Mathematically, singularities exist at any point in the workspace where the Jacobian matrix loses rank. a matrix is singular if and only if its determinant is zero: det(j) =0

(6 x 1) body velocity (n x 1) joint velocities (6 x n) Jacobian For a 6-DOF manipulator with a spherical wrist, we can decouple the determination of singular configurations into two simpler problems.

Singular when any two wrist axes align

Manipulability For a specific configuration, the Jacobian scales the input (joint velocities) to the output (body velocity) If you put in a joint velocity vector with unit norm, you can calculate in which direction and how fast the robot will translate and rotate. If the Jacobian is full rank, you can calculate the manipulability ellipsoid. If not redundant, manipulability

What does the manipulability ellipsoid look like for the planar RR robot? (x, y) a 2 θ 2 a 1 θ 1

Can be used to tell you where to perform certain tasks. Also useful for deciding how to design a manipulator.

Soon I will release Homework 4, an individual assignment on Jacobians Not sure when it will be due...

Homework 2 and 3 graded