Exploiting Spherical Projections To Generate Human-Like Wrist Pointing Movements

TL;DR

This paper introduces a novel approach using spherical projections and fractal impedance control to generate human-like wrist pointing movements efficiently, avoiding complex inverse problems.

Contribution

It presents a new method combining spherical projections with PMP and fractal impedance control to produce human-like wrist movements without nonlinear inverse optimization.

Findings

Path-independent wrist movements explained by spherical projections.

Reduced computational cost compared to previous methods.

Elimination of nonlinear inverse problems in movement generation.

Abstract

The mechanism behind the generation of human movements is of great interest in many fields (e.g. robotics and neuroscience) to improve therapies and technologies. Optimal Feedback Control (OFC) and Passive Motion Paradigm (PMP) are currently two leading theories capable of effectively producing human-like motions, but they require solving nonlinear inverse problems to find a solution. The main benefit of using PMP is the possibility of generating path-independent movements consistent with the stereotypical behaviour observed in humans, while the equivalent OFC formulation is path-dependent. Our results demonstrate how the path-independent behaviour observed for the wrist pointing task can be explained by spherical projections of the planar tasks. The combination of the projections with the fractal impedance controller eliminates the nonlinear inverse problem, which reduces the computational cost compared to previous methodologies. The motion exploits a recently proposed PMP architecture that replaces the nonlinear inverse optimisation with a nonlinear anisotropic stiffness impedance profile generated by the Fractal Impedance Controller, reducing the computational cost and not requiring a task-dependent optimisation.