Haptic force fields are widely used in studies on motor adaptation, motor retention, and motor recovery in both healthy and impaired subjects. In the main paradigm the hand is guided or perturbed along specific paths or channels in order to investigate different aspects underlying the human motor control. Programming such fields for complex haptic environments can be very challenging and is often not feasible for clinicians and therapists. The aim of this paper is to introduce a more intuitive and clinician-friendly programming method capable of transforming a 2D drawing (stored as an image) into a haptic environment or planar force field. By considering the image intensity as a position-dependent potential field, the energy function is approximated through locally weighted projection regression (LWPR). Robot forces are then computed through the gradient of the regressed potential. The proposed method is validated with a two degrees-of-freedom planar manipulandum, the H-Man, and a preliminary shape recognition experiment involving blindfolded healthy subjects.
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