International Journal on Advanced Science, Engineering and Information Technology, Vol. 12 (2022) No. 2, pages: 501-507, DOI:10.18517/ijaseit.12.2.15289

Gravitational Base Parameters Identification for a Knee Rehabilitation Parallel Robot

Pulloquinga José L., Escarabajal Rafael J., Mata Vicente, Valera Ángel, Zambrano Iván, Rosales Andres


New robotic technology is emerging nowadays to tackle lower limb rehabilitation issues. However, the commercial robots available for lower limb rehabilitation are usually oversize and expensive. Knee rehabilitation is generally aided by a professional therapist, making this clinical procedure an interesting scope for robotics. Parallel robots are suitable candidates for knee rehabilitation due to their high load capacity, stiffness, and accuracy compared to serial ones. In contrast, this robot has singular configurations inside its workspace, and its dynamic model is generally complex. For these reasons, a parallel robot for knee rehabilitation needs an advanced control unit to solve complex mathematical problems that ensure patient security. This study proposes the base parameters identification of a compact gravitational linear model of a 3UPS+RPU parallel robot using singular value decomposition. This paper recommends adding a statistical method focused on condition number minimization to the singular value decomposition process. This statistical method reduces the computational resources taken searching for the best inertial parameters combination at the beginning of the base parameter identification. The gravitational base parameters identified have a physical meaning and low complexity. This fact makes the results of this research the basis of an adaptative control applied to 3UPS+RPU parallel robot. This study shows that the gravitational term is the most influential for knee rehabilitation tasks, compared with the inertial, Coriolis, and centrifugal components, regarding the dynamic behavior of the parallel robot.


Base parameter; identification; parallel robot; knee rehabilitation; model-based control.

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