This paper presents a novel contour tracking scheme based on a well-posed kinematic representation of differential-driven nonholonomic mobile robots. Firstly, a fuzzy aggregation of spatial sets in cluttered environments allows designing a velocity field to encode the desired velocity vector pointing to the target (the contour). Thus, the resultant smooth trajectory avoids obstacles by combining spatially distributed velocity fields that enable the robot navigation. Finally, the universal approximation property of fuzzy systems facilitates the design of an adaptive PI-like controller, whose closed-loop stability leads to the precise tracking of the velocity field. The results of the performed numerical simulations illustrate the reliability of the proposed scheme.
Our 15 years of research have generated the first short- and long-term efficacy data for speech treatment (Lee Silverman Voice Treatment; LSVT/LOUD) in Parkinson's disease. We have learned that training the single motor control parameter amplitude (vocal loudness) and recalibration of self-perception of vocal loudness are fundamental elements underlying treatment success. This training requires intensive, high-effort exercise combined with a single, functionally relevant target (loudness) taught across simple to complex speech tasks. We have documented that training vocal loudness results in distributed effects of improved articulation, facial expression, and swallowing. Furthermore, positive effects of LSVT/LOUD have been documented in disorders other than Parkinson's disease (stroke, cerebral palsy). The purpose of this article is to elucidate the potential of a single target in treatment to encourage cross-system improvements across seemingly diverse motor systems and to discuss key elements in mode of delivery of treatment that are consistent with principles of neural plasticity. 2b1af7f3a8