In medical contexts, the use of assistive exoskeletons for the rehabilitation of people with impaired mobility represents a common practice. Recent advances suggest that, soon, such mechatronic systems will also be used to assist people in their everyday life. In order to reach such target, exoskeletons must become able to perceive the environment. To this purpose, a system for the parametric identification of a staircase is proposed in this paper. More precisely, given a staircase of unknown geometry, the system identifies its 3D shape. Furthermore, it also estimates the reciprocal orientation and distance between the exoskeleton and the staircase. Differently from other approaches, this result is achieved by means of low cost devices: an inertial measurement unit, two ranging sensors, and an Arm-Cortex processor. Starting from the ranging sensors acquisitions, the staircase model is identified in real time, during the execution of a step. The proposed procedure is based on an extended recursive total least squares strategy, in order to fully exploit the computational capabilities of the Arm processor, and it is characterized by execution times smaller than 10 −3 s. The estimation algorithm has been tested on an actual exoskeleton and the resulting experimental outcomes are compared with the results obtained through alternative methods.
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