Year: 2016
Type: preprint
Abstract: This paper demonstrates simultaneous identification and control of the humanoid robot, Valkyrie, utilizing Spatial Vector Algebra (SVA). In particular, the inertia, Coriolis-centrifugal and gravity terms for the dynamics of a robot are computed using spatial inertia tensors. With the assumption that the link lengths or the distance between the joint axes are accurately known, it will be shown that inertial properties of a robot can be directly evaluated from the inertia tensor. An algorithm is proposed to evaluate the regressor, yielding a run time of $O(n^2)$. The efficiency of this algorithm yields a means for online system identification via the SVA--based regressor and, as a byproduct, a method for accurate model-based control. Experimental validation of the proposed method is provided through its implementation in three case studies: offline identification of a double pendulum and a $4$-DOF robotic leg, and online identification and control of a $4$-DOF robotic arm.
Source: arXiv (Cornell University)
Institution: Texas A&M University
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Awards: CPS: Medium: Collaborative Research: A CPS Approach to Robot Design, THE APPLICANT PROPOSES TO BRING TEXAS A&M UNIVERSITY AMBER LAB'S PERSPECTIVE ON THE CONTROL OF BIPEDAL WALKING TO NASA'S ROBONAUT 2 PROGRAM. THE AMBE, CAREER: Closing the Loop on Walking: From Hybrid Systems to Bipedal Robots to Prosthetic Devices and Back
OpenAlex ID: W2521598842