Optimization of a Reconfigurable Manipulator with Lockable Cylindrical Joints

This thesis presents a global optimization methodology to find the optimal Denavit-Hartenbeg parameters of a serial reconfigurable robotic manipulator maximizing a cost function over a pre-specified workspace volume and given lower and upper bounds on the design parameters. Several cost functions are investigated such as the manipulability measure, maximum force/torque capability of the manipulator at its end-effector, and maximum velocity capability of the manipulator, therefore improving the general kinetostatic performance of the manipulator. A modified global and posture-independent parameter of singularity (MPIPS) is presented, and a generic global optimization approach is proposed, using combined genetic algorithm (GA) and sequential quadratic programming (SQP). Different case studies are provided for a 3-DOF and a 6-DOF reconfigurable manipulator. Finally, a weighted objective function that balances between the opposing actions of the end effector velocity and force is proposed. The results are illustrated to demonstrate the performance of the generated manipulators, and are validated. Post-optimality analysis has also been conducted to investigate the sensitivity of the index to the variation in optimal parameters