Planar soft space robotic manipulators: Dynamic modeling and control

Abstract

Space robots have proven their ability to accomplish many space missions impossible or dangerous for the human. However, the conventional space robots suffer from the low adaptability, heavy structures, and the low safety. In this regard, the bio-inspired soft robots, composed of the soft material, have been emerged to overcome these shortcomings and to expand the space missions’ diversity. The potential of soft robots for space applications has recently been investigated in the literature. Although the dynamic modeling and control of soft robotic arms are complicated due to their infinite degrees of freedom, soft manipulators are anticipated to provide the adaptive capture of targets, confined space operations, and the long-distance handling of space facilities. In this regard, a general novel dynamic modeling algorithm is presented here for soft space robotic manipulators (SSRM) in a specified orientation based on the generalized Jacobian method. The proposed algorithm could be employed for different numbers of soft manipulator constant-curvature elements and avoids numerical singularities using the Taylor expansion as well. In addition, the generalized Jacobian matrix is defined to compute the velocity of any arbitrary point on the soft manipulator for contact dynamics objectives. Accuracy of the proposed dynamic model has been verified via comparison to the simulation results of the existing fixed-base soft manipulators. Moreover, performance of the proposed model has been more investigated through two numerical simulation case studies. The first case verifies that the dynamic responses of the floating SSRM follows the physical principles. While the second one addresses the configuration tracking problem of the floating SSRM exposing a computed torque control scheme. The obtained results indicate the effectiveness of the presented dynamic modeling algorithm and the proposed control scheme.