Many authors have been working on approaches that can be applied to social robots to allow a more realistic/comfortable relationship between humans and robots in the same space. This paper proposes a new navigation strategy for social environments by recognizing and considering the social conventions of people and groups. To achieve that, we proposed the application of Delaunay triangulation for connecting people as vertices of a triangle network. Then, we defined a complete asymmetric Gaussian function (for individuals and groups) to decide zones where the robot must avoid passing. Furthermore, a feature generalization scheme called socialization feature was proposed to incorporate perception information that can be used to change the variance of the Gaussian function. Simulation results have been presented to demonstrate that the proposed approach can modify the path according to the perception of the robot compared to a standard A* algorithm.
Shunt active power filters (SAP F) implemented without harmonic detection schemes compensate the harmonic distortion and reactive power of the load simultaneously. However, their compensation capabilities are limited by the SAP F power converter rating. Such a restriction can be minimized if the level of the reactive power demanded by the SAP F is managed. An estimation scheme for determining the filter currents is introduced to manage the level of reactive power compensation. The effectiveness of the proposed control strategy is ensured by introducing a feedforward scheme on the DC-link voltage regulation. In addition, a robust control based on adaptive pole placement with a variable structure scheme regulates the grid currents. Experimental results are shown for demonstrating the effectiveness of the proposed SAP F system.
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