A Vision-based Computed Torque Control for Parallel Kinematic Machines

TL;DR

This paper introduces a novel vision-based computed torque control method for parallel kinematic machines, simplifying model complexity and demonstrating improved performance through simulations and experiments on the Orthoglide robot.

Contribution

It presents a new control approach that uses only end-effector pose and exteroceptive measures, reducing model and control scheme complexity for parallel robots.

Findings

Enhanced control performance demonstrated in simulations

Practical feasibility confirmed through experiments

Reduced model complexity achieved

Abstract

In this paper, a novel approach for parallel kinematic machine control relying on a fast exteroceptive measure is implemented and validated on the Orthoglide robot. This approach begins with rewriting the robot models as a function of the only end-effector pose. It is shown that such an operation reduces the model complexity. Then, this approach uses a classical Cartesian space computed torque control with a fast exteroceptive measure, reducing the control schemes complexity. Simulation results are given to show the expected performance improvements and experiments prove the practical feasibility of the approach.