Interactive communication human-robot interface for reduced mobility people assistance

Abstract

Communication between a robot and its user is essential for the execution of tasks, even more so in a scenario where the robot is designed to assist people with reduced mobility. This document presents the evaluation of a conversation script between a human user and a robot for assistance using pre-recorded responses, for this a methodology with three phases was proposed and applied: establishment of the training scheme of a convolutional network that allows recognize user's words for execution of tasks by the robot, generation of dialogue between the user and possible interactions with the assistive robot and finally, the measurement of perception of interface users. Results show a high level of accuracy with words selected to command the robot, using a convolutional neural network, with an audio input discriminated in its components mel frequency cepstral coefficients (MFCCs) and command sets of male and female voices. It was possible to establish a dialogue model with three scenes to recognize the residential environment, rename spaces and execute action commands to move elements. It is concluded the designed instrument is reliable and the perception of proposed interactive communication interface is good in terms of usability (effectiveness, efficiency, and user satisfaction).