Kinematics and Optimal Control of a Mobile Parallel Robot for Inspection of Pipe-like Environments

Abstract

The objective of this thesis is to analyze the kinematics of a mobile parallel robot with contribution that pertain to the singularity analysis, the optimization of geometric parameters and the optimal control to avoid singularities when navigating across singular geometric configurations. The analysis of the workspace and singularities is performed in a prescribed reference workspace regions using discretization method. Serial and parallel singularities are analytically analyzed and all possible singular configurations are presented. Kinematic conditioning index is used to determine the robot’s proximity to a singular configuration. A method for the determination of a continuous and singularity-free workspace is detailed. The geometric parameters of the system are optimized in various types of pipe-like structures with respect to a suitable singularity index, in order to avoid singularities during the navigation across elbows. The optimization problem is formulated with an objective to maximize the reachable workspace and minimize the singularities. The objective function is also subjected to constraints such as collision avoidance, singularity avoidance, workspace continuity and contact constraints imposed between the boundaries and the wheels of the robot. A parametric variation method is used as a technique to optimize the design parameters. The optimal design parameters found are normalized with respect to the width of the pipe-like structures and therefore the results are generalized to be used in the development phase of the robot. An optimal control to generate singularity-free trajectories when the robotic device has to cross a geometric singularity in a sharp 90◦ elbow is proposed. Such geometric singularity inherently leads to singularities in the Jacobian of the system, and therefore a modified device with augmented number of degrees of freedom is introduced to be able to generate non-singular trajectories.