Design and evaluation of sound-based electronic football soccer training system for visually impaired athletes.

BACKGROUND: Several countries encourage the practice of football for rehabilitation and social inclusion purposes. For visually impaired people, football is purely sound-based, where the ball and the players are constantly emitting sounds for localization purposes in the field. However, the task of shooting the ball requires of a non-visually impaired extra person, behind the goal (known as caller), whom is punching the four corner of such goal to help the athletes. The presence of the caller restricts the self-sufficiency of the players. This work addresses such problem, by presenting a goal for visually impaired players with the aim of enhancing their self-sufficiency. MATERIALS AND METHODS: The electronic goal is designed with four functionalities for training purposes, by returning sound-based feedback of its position and the places where the ball has impacted. The system is validated with seven volunteers from Chilean Football Soccer National Team. A questionnaire was answered by the players before and after the tests to statically validate the proposed device. RESULTS: The presented system is portable and designed following a modular criterion suitable for visually impaired people self-assembling. From a test of 350 shootings, the electronic goal showed to enhance the shooting assertiveness from 82 to 92%, and the accuracy from 20 to 56% compared to the traditional caller. CONCLUSIONS: The electronic goal showed to enhance the self-sufficiency of athletes, by improving their assertiveness in shooting training. Nevertheless, and according to the responses to the questionnaires, the system needs improvements in its portability and handling.

Ultra wide-band localization and SLAM: a comparative study for mobile robot navigation.

In this work, a comparative study between an Ultra Wide-Band (UWB) localization system and a Simultaneous Localization and Mapping (SLAM) algorithm is presented. Due to its high bandwidth and short pulses length, UWB potentially allows great accuracy in range measurements based on Time of Arrival (TOA) estimation. SLAM algorithms recursively estimates the map of an environment and the pose (position and orientation) of a mobile robot within that environment. The comparative study presented here involves the performance analysis of implementing in parallel an UWB localization based system and a SLAM algorithm on a mobile robot navigating within an environment. Real time results as well as error analysis are also shown in this work.

Analysis of different feature selection criteria based on a covariance convergence perspective for a SLAM algorithm.

This paper introduces several non-arbitrary feature selection techniques for a Simultaneous Localization and Mapping (SLAM) algorithm. The feature selection criteria are based on the determination of the most significant features from a SLAM convergence perspective. The SLAM algorithm implemented in this work is a sequential EKF (Extended Kalman filter) SLAM. The feature selection criteria are applied on the correction stage of the SLAM algorithm, restricting it to correct the SLAM algorithm with the most significant features. This restriction also causes a decrement in the processing time of the SLAM. Several experiments with a mobile robot are shown in this work. The experiments concern the map reconstruction and a comparison between the different proposed techniques performance. The experiments were carried out at an outdoor environment composed by trees, although the results shown herein are not restricted to a special type of features.