Exponential Coordinates of Rigid-Body Motion (Chapter 3.3.3)

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From the course by Northwestern University

Modern Robotics, Course 1: Foundations of Robot Motion

136 ratings

Northwestern University

Modern Robotics, Course 1: Foundations of Robot Motion

136 ratings

Course 1 of 6 in the Specialization Modern Robotics: Mechanics, Planning, and Control

Do you want to know how robots work? Are you interested in robotics as a career? Are you willing to invest the effort to learn fundamental mathematical modeling techniques that are used in all subfields of robotics? If so, then the "Modern Robotics: Mechanics, Planning, and Control" specialization may be for you. This specialization, consisting of six short courses, is serious preparation for serious students who hope to work in the field of robotics or to undertake advanced study. It is not a sampler. In Course 1 of the specialization, Foundations of Robot Motion, you will learn fundamental material regarding robot configurations, for both serial robot mechanisms and robots with closed chains. You will learn about configuration space (C-space), degrees of freedom, C-space topology, implicit and explicit representations of configurations, and holonomic and nonholonomic constraints. You will also learn how to represent spatial velocities and forces as twists and wrenches. This material is at the core of the study of anything that moves (e.g., robots). This course follows the textbook "Modern Robotics: Mechanics, Planning, and Control" (Lynch and Park, Cambridge University Press 2017). You can purchase the book or use the free preprint pdf. You will build on a library of robotics software in the language of your choice (among Python, Mathematica, and MATLAB) and use the free cross-platform robot simulator V-REP, which allows you to work with state-of-the-art robots in the comfort of your own home and with zero financial investment.

From the lesson

Chapter 3: Rigid-Body Motions (Part 2 of 2)

Homogeneous transformation matrices, twists, screws, exponential coordinates of rigid-body motion, and wrenches.

Homogeneous Transformation Matrices (Chapter 3.3 through 3.3.1)6:21

Twists (Chapter 3.3.2, Part 1 of 2)4:59

Twists (Chapter 3.3.2, Part 2 of 2)2:38

Exponential Coordinates of Rigid-Body Motion (Chapter 3.3.3)4:59

Wrenches (Chapter 3.4)3:00

Meet the Instructors

Kevin Lynch
Professor
Mechanical Engineering

In the previous videos, we learned that any instantaneous velocity of a rigid body can

be represented as a twist, defined by a speed theta-dot rotating about, or translating along,

a screw axis S. In this video, we integrate the vector differential equation describing

the motion of a frame twisting along a constant screw axis to find the final displacement

of the frame.

This animation shows a screw axis S and a frame at time zero.

Let's say that this configuration is coincident with the space frame {s}, so its representation

is the identity matrix.

Now we let the frame twist about the screw axis at a rotational speed theta-dot = 1.

The animation shows the configuration achieved at times t equals pi and t equals 2 pi.

These configurations are represented as transformation matrices, but an alternative representation

would use 6 exponential coordinates, similar to the 3 exponential coordinates for rotation

that we saw earlier.

In this case, we could represent the configuration at time pi as S times pi, meaning the configuration

achieved after the frame has followed the screw axis S for time pi.

Similarly, we could represent the configuration at time 2 pi as S times 2 pi.

Let's look at some of the analogies between rotations and full rigid-body motions.

For rotations, we have a unit rotation axis omega-hat.

For rigid-body motions, we have a screw axis where either the angular component is a unit

vector or the angular component is zero and the linear component is a unit vector.

For rotations, the exponential coordinates are omega-hat theta, where theta is the angle

of rotation about the axis omega-hat.

For rigid-body motions, the exponential coordinates are S-theta.

If the screw axis has any angular component, theta is the angle rotated about the screw

axis.

If the screw axis has zero rotation, then theta is the linear distance traveled along

the axis.

For rotations, the matrix representation of the exponential coordinates is the 3 by 3

skew symmetric representation of omega-hat times theta.

The set of all such matrices is called little so(3).

For rigid-body motions, the matrix representation of the exponential coordinates is a 4 by 4

matrix in little se(3), which we learned about in the last video.

For rotations, the exponential maps matrices in little so(3) to rotation matrices, and

the log maps rotation matrices to little so(3).

For rigid-body motions, the exponential maps matrices in little se(3) to transformation

matrices, and the log maps transformation matrices to little se(3).

As with the case for rotations, the matrix exponential for rigid-body motions has closed-form

solutions.

There are two cases to consider: one where the screw axis is a pure translation with

no rotation, and one where the screw axis has rotation.

For the case of a purely translational screw axis, theta refers to the linear distance

traveled, and the solution is particularly simple: the orientation is unchanged, hence

the identity matrix in the top left submatrix, and the new position is just the unit linear

velocity of the screw axis times the distance traveled.

For the case of a screw axis with rotation, again a closed-form solution exists, but it

is a bit more complicated.

The algorithm for the matrix logarithm involves inverting these expressions to find the matrix

representation of the exponential coordinates S times theta.

Now, given a body frame {b} at the configuration T_sb relative to the space frame {s}, we would

like to know the final configuration T_sb-prime of the body frame if it travels a distance

theta along the screw S. We could represent S in either the {s} frame or the {b} frame.

If we define it in the {b} frame, the final configuration T_sb prime is T_sb times the

matrix exponential.

Remembering that multiplying by a transformation on the right corresponds to a transformation

expressed in the frame of the second subscript.

If we define the screw axis in the {s} frame, we must premultiply T_sb by the matrix exponential,

since multiplication on the left means that the transformation is expressed in the frame

of the first subscript.

Each single-degree-of-freedom joint of a robot, such as a revolute joint, a prismatic joint,

or a helical joint, has a joint axis defined by a screw axis.

The matrix exponential and log will be used extensively in the study of robot kinematics,

starting in Chapter 4.

The next and final video of Chapter 3 covers the representation of forces and torques in

three-dimensional space.

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