COMPARISON OF PARALLEL COMPUTATION SCHEMES FOR CALCULATING ROBOT JACOBIANS

The paper addresses a point of major difficulty in designing robot control algorithms; that of computing the kinematic Jacobian matrix and its inverse on-line. Various techniques for calculating the forward and inverse Jacobian have been modified into a form optimized for parallel processing. The important problem of singularities in the robot configuration has also been considered, and robust matrix inversion techniques are proposed for this case. All algorithms have been implemented on transputer networks and computation times measured. The paper emphasises the importance of including communication overheads in comparisons of the computational efficiency of alternative algorithms and processor networks. Theoretical processing times based on computer cycle times and arithmetic operation counts are shown to be a false basis for comparison. Whilst considering the specific case of computation of Jacobian matrices for a robot manipulator, the paper provides a useful example of the considerations and constraints involved in distributing any algorithm across a multi-processor network.