Multi-Objective Trajectory Planning of Mobile Parallel Manipulator.

摘要

This thesis studies a new generation of robotic systems; Mobile Parallel Manipulator (MPM); these are composed of a multi-degree of freedom parallel platform carried by an autonomous wheeled mobile robot. Both position and differential kinematics problems are solved in details. The problems of kinematic singularity and redundancy are solved through joint limits avoidance and manipulability criteria. Furthermore, taking the MPM self motion into consideration due to its redundancy, the inverse kinematic is derived using hybrid neuro-fuzzy system called NeFIK. The discrete Augmented Lagrangean (AL) technique is then used to solve the highly nonlinear constrained multi-objective optimal control problem. Based on the result of the AL solution, an ANFIS based structure is built to solve for the online trajectory planning of the MPM. Result of both offline and online shows that the trajectory planning of MPM is derived with small acceptable error.