Hamano, Fumio

This thesis presents several algorithms to treat the problem
of closed-loop near minimum-time controls with
discontinuities. First, a neighboring control algorithm is
developed to solve the problem in which controls are bounded
by constant constraints. Secondly, the scheme is extended
to account for state-dependent control constraints. And
finally, a path tracking algorithm for robotic manipulators
is presented, which is also a neighboring control algorithm.
These algorithms are suitable for real time controls because
the on-line computations involved are relatively simple.
Simulation results show that these algorithms work well
despite the fact that the prescribed final points can not be
reached exactly.

Theoretical and practical issues of kinematic modeling, measurement, identification and compensation are addressed in this dissertation. A comprehensive robot calibration methodology using a new Complete and Parametrically Continuous (CPC) kinematic model is presented. The dissertation focuses on model-based robot calibration techniques. Parametric continuity of a kinematic model is defined and discussed to characterize model singularity. Irreducibility is defined to facilitate error model reduction. Issues of kinematic parameter identification are addressed by utilizing generic forms of linearized kinematic error models. The CPC model is a complete and parametrically continuous kinematic model capable of describing geometry and motion of a robot manipulator. Owing to the completeness of the CPC model, the transformation from the base frame to the world frame and from the tool frame to the last link frame can be modeled with the same modeling convention as the one used for internal link transformations. Due to the parametric continuity of the CPC model, numerical difficulties in kinematic parameter identification using error models are reduced. The CPC model construction, computation of the link parameters from a given link transformation, inverse kinematics, transformations between the CPC model and the Denavit-Hartenberg model, and linearized CPC error model construction are investigated. New methods for self-calibration of a laser tracking coordinate-measuring-machine are reported. Two calibration methods, one based on a four-tracker system and the other based on three trackers with a precision plane, are proposed. Iterative estimation algorithms along with simulation results are presented. Linear quadratic regulator (LQR) theory is applied to design robot accuracy compensators. In the LQR algorithm, additive corrections of joint commands are found without explicitly solving the inverse kinematic problem for an actual robot; a weighting matrix and coefficients in the cost function can be chosen systematically to achieve specific objective such as emphasizing the positioning accuracy of the end-effector over its orientation accuracy and vice versa and taking into account joint travelling limits as well as singularity zones of the robot. The results of the kinematic identification and compensation experiments using the PUMA robot have shown that the CPC modeling technique presented in this dissertation is a convenient and effective means for accuracy improvements of industrial robots.