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RESOLVED MOTION CONTROL FOR HIGH-DEGREE-OF-FREEDOM ARTICULATED FIGURES
S.K. Semwal and D. Bolt
References
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[43] M.W. Walker, & D.E. Orin, Efficient dynamic computer simulation of robotic mechanisms, Journal of Dynamic Systems, Measurement, and Control, 104, September 1982, 205–211. Appendix A Pseudoinverse Jacobian Using Singular Value Decomposition Articulated Figure Model The articulated figure model is specified by geometry, a density factor, and joint positions. The density is set to be equal to the density of water. Geometry is accepted in the popular DXF file format. A naming convention for objects in the file gives the joint information. The integral properties (mass, centre of mass, inertia matrix) for each link of the model are automatically calculated when the model is imported using the technique described in [34]. Computing the trajectory of motion using standard curves 313 and free body diagrams are explained in [34] and also in [40]. Details of Jacobian matric for a simple chain of singleDOF joints, multiple-DOF joints, and tree structures with and without shared links can also be found in [34] and are not explained here due to space limitations. The main idea of finding the pseudoinverse is explained below. If the Jacobian J were square (N = M = 6 degrees of freedom) and nonsingular for the current joint space configuration, then for a desired end-effector velocity we could directly compute the joint space velocity vector by inverting the Jacobian: q = J−1 ˆvn (A1) In our case the articulated figure has redundant degrees of freedom (N > 6). The Jacobian cannot be inverted directly. Instead of a one-to-one relationship between the joint space and end-effector velocities there is a subspace of joint velocities that will result in the desired end-effector velocity. We determine the pseudoinverse of the Jacobian using singular value decomposition (SVD) [41, 42]. SVD states than any M × N matrix J can be written as a product of an M × N column-orthogonal matrix U, an N × N diagonal matrix W with positive or zero elements, and the transpose of an N × N orthogonal matrix V (A2). The orthogonality requirements on U and V provide that UT U = VT V = I. [J]M×N = [U]M×N w1 0 w2 . . . 0 wN N×N [V T ]N×N (A2) SVD constructs ortho-normal bases for the range and null-space of J in the matrices U and V respectively. If wi > 0 then column i from U is a basis vector for the range of J. If wi = 0 then column i from V is a basis vector for the nullspace of J. We expect J to have a nullity (nullity = dimension(nullspace(J))) of N − M and a rank (rankdimension(range(J))) of M. If a joint is fully extended then J will also have a singular value associated with this degeneracy. Consequently, the range is reduced by 1 and nullity is increased by 1. The pseudoinverse of J is given by equation (A3). [J−1 ]N×M = [V ]N×M 1 w1 0 1 w2 . . . 0 1 wN N×N [UT ]N×M 1 wi = 0 if wi < ε (A3) Or: J−1 = V · d iag 1 wi · UT 1 wi = 0 if wi < ε where 1/wi is replaced with 0 if wi = 0 (or close to zero due to rounding error). The solution to (A1) is: q = J−1 ˆv = V · d iag 1 wi · (UT · ˆv) 1 wi = 0 if wi < ε (A4) As M < N there are in general an infinite number of solutions to (A5). Different solutions are obtained by adding vectors from the nullspace of J to q . (A8) gives the solution vector of smallest length. Thus, the minimum (in the least squares sense) joint space velocity vector solution q i s obtained by (A8). Insofar as joint velocity represents kinetic energy, (A8) gives a locally optimal kinetic energy solution to the desired motion. Singularities and Solutions: Unreachable Configurations With our error control algorithm it is required that all end-effector positions be reachable. If a position is not reachable the algorithm will terminate at the unachievable frame. The COM path optimization algorithms comfort term in the objective will help to prevent these situations. The COM path could also be altered if an unreachable situation were encountered during the joint space trajectory computation. For example, the Z nominal (see Section 3 above) value for the failing COM path spline could be altered and the COM path optimization revisited for that spline. Of course, the full joint space computation could be executed during the COM path optimization with objective functions added based on the result of the joint solutions. Nearly Unreachable Configurations If a point on the COM path presents a configuration where the figure must stretch to reach a target end-effector location, then one or more joints may reach a fully straightened condition. When a joint is in its fully extended state the figure essentially losses the DOF associated with that joint. Mathematically, the Jacobian matrix will have a singularity, which will result in large joint velocities for a small end-effector velocity. This can cause the joint configuration to attain an awkward pose. As the joint space computation attempts to minimize the joint velocities, the figure will tend to stay in its current pose. Thus if a near-unreachable position is encountered the figure will be thrown into an awkward pose and not recover for the rest of the sequence. Once again avoidance of these situations is one solution. The pseudoinverse of the Jacobian could also be replaced by a more robust computation for singularities such as the Singularity Robust Inverse in [27, 43]. A method for biasing joints towards a desired quiescent position during the joint position computation could also be tried. 314 Joint Limitations The current implementation does not provide for limits on joint angles. A knee could bend backwards, for instance. As mentioned above, the pseudoinverse of the Jacobian tends to keep joints near their starting position. As steps must be taken to keep joints from reaching a singularity, these same steps will keep a joint, such as a knee, from bending backwards. It still would be desirable to be able to limit joint travel. It may be desirable, for example, to limit the hip joint to a 10 degree travel range. Joint limitations details are discussed in [41]. Sample snapshots of our implementation are shown below.
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DOI:
10.2316/Journal.205.2006.4.205-4265
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(205) International Journal of Modelling and Simulation - 2006
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