Robot Modeling and Control. Mark W. Spong. Читать онлайн. Newlib. NEWLIB.NET

Автор: Mark W. Spong
Издательство: John Wiley & Sons Limited
Серия:
Жанр произведения: Техническая литература
Год издания: 0
isbn: 9781119524045
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and be the vector from the origin of frame o0x0y0z0 to the origin of frame o1x1y1z1. Suppose the point is rigidly attached to coordinate frame o1x1y1z1, with local coordinates . We can express the coordinates of with respect to frame o0x0y0z0 using

      and

      The composition of these two equations defines a third rigid motion, which we can describe by substituting the expression for from Equation (2.59) into Equation (2.60)

      Since the relationship between and is also a rigid motion, we can equally describe it as

      Comparing Equations (2.61) and (2.62) we have the relationships

      Equation (2.63) shows that the orientation transformations can simply be multiplied together and Equation (2.64) shows that the vector from the origin o0 to the origin o2 has coordinates given by the sum of (the vector from o0 to o1 expressed with respect to o0x0y0z0) and (the vector from o1 to o2, expressed in the orientation of the coordinate frame o0x0y0z0).

      2.6.1 Homogeneous Transformations

      One can easily see that the calculation leading to Equation (2.61) would quickly become intractable if a long sequence of rigid motions were considered. In this section we show how rigid motions can be represented in matrix form so that composition of rigid motions can be reduced to matrix multiplication as was the case for composition of rotations.

      In fact, a comparison of Equations (2.63) and (2.64) with the matrix identity

      (2.65)numbered Display Equation

      Transformation matrices of the form given in Equation (2.66) are called homogeneous transformations. A homogeneous transformation is therefore nothing more than a matrix representation of a rigid motion and we will use SE(3) interchangeably to represent both the set of rigid motions and the set of all 4 × 4 matrices of the form given in Equation (2.66).

      Using the fact that is orthogonal it is an easy exercise to show that the inverse transformation is given by

      In order to represent the transformation given in Equation (2.58) by a matrix multiplication, we must augment the vectors and by the addition of a fourth component of 1 as follows,

      (2.68)numbered Display Equation

      (2.69)numbered Display Equation

      The vectors and are known as homogeneous representations of the vectors Скачать книгу