A BDI architecture for high level robot deliberation

In this work we present a BDI agent architecture used for high level reasoning agents that control mobile robots that play soccer. This architecture is build on top of layered system, where each of these layers is associated with a di®erent level of abstraction. The proposed approach allows the speci¯cation of declarative goal driven robot behavior, that uses sophisticated high level reasoning and reactivity when needed. The elements of mental components are studied with their interaction and their syntaxis and semantics are de¯ned.Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Systematic literature review of realistic simulators applied in educational robotics context

This paper presents a systematic literature review (SLR) about realistic simulators that can be applied in an educational robotics context. These simulators must include the simulation of actuators and sensors, the ability to simulate robots and their environment. During this systematic review of the literature, 559 articles were extracted from six different databases using the Population, Intervention, Comparison, Outcomes, Context (PICOC) method. After the selection process, 50 selected articles were included in this review. Several simulators were found and their features were also analyzed. As a result of this process, four realistic simulators were applied in the review’s referred context for two main reasons. The first reason is that these simulators have high fidelity in the robots’ visual modeling due to the 3D rendering engines and the second reason is because they apply physics engines, allowing the robot’s interaction with the environment.info:eu-repo/semantics/publishedVersio

A comparison of fuzzy approaches for training a humanoid robotic football player

© 2017 IEEE. Fuzzy Systems are an efficient instrument to create efficient and transparent models of the behavior of complex dynamic systems such as autonomous humanoid robots. The human interpretability of these models is particularly significant when it is applied to the cognitive robotics research, in which the models are designed to study the behaviors and produce a better understanding of the underlying processes of the cognitive development. From this research point of view, this paper presents a comparative study on training fuzzy based system to control the autonomous navigation and task execution of a humanoid robot controlled in a soccer scenario. Examples of sensor data are collected via a computer simulation, then we compare the performance of several fuzzy algorithms able to learn and optimize the humanoid robot's actions from the data