Modeling a mobile robot using a grammatical model

Virtual Worlds Generator is a grammatical model that is proposed to define virtual worlds. It integrates the diversity of sensors and interaction devices, multimodality and a virtual simulation system. Its grammar allows the definition and abstraction in symbols strings of the scenes of the virtual world, independently of the hardware that is used to represent the world or to interact with it. A case study is presented to explain how to use the proposed model to formalize a robot navigation system with multimodal perception and a hybrid control scheme of the robot.

A grammatical approach to the modeling of an autonomous robot

Virtual Worlds Generator is a grammatical model that is proposed to define virtual worlds. It integrates the diversity of sensors and interaction devices, multimodality and a virtual simulation system. Its grammar allows the definition and abstraction in symbols strings of the scenes of the virtual world, independently of the hardware that is used to represent the world or to interact with it. A case study is presented to explain how to use the proposed model to formalize a robot navigation system with multimodal perception and a hybrid control scheme of the robot. The result is an instance of the model grammar that implements the robotic system and is independent of the sensing devices used for perception and interaction. As a conclusion the Virtual Worlds Generator adds value in the simulation of virtual worlds since the definition can be done formally and independently of the peculiarities of the supporting devices.

New insights into plant salt acclimation: the roles of vesicle trafficking and reactive oxygen species signalling in mitochondria and the endomembrane system

In this study, we investigated the cellular and molecular mechanisms that regulate salt acclimation. The main objective was to obtain new insights into the molecular mechanisms that control salt acclimation. Therefore, we carried out a multidisciplinary study using proteomic, transcriptomic, subcellular and physiological techniques. We obtained a Nicotiana tabacum BY-2 cell line acclimated to be grown at 258 mM NaCl as a model for this study. The proteomic and transcriptomic data indicate that the molecular response to stress (chaperones, defence proteins, etc.) is highly induced in these salt-acclimated cells. The subcellular results show that salt induces sodium compartmentalization in the cell vacuoles and seems to be mediated by vesicle trafficking in tobacco salt-acclimated cells. Our results demonstrate that abscisic acid (ABA) and proline metabolism are crucial in the cellular signalling of salt acclimation, probably regulating reactive oxygen species (ROS) production in the mitochondria. ROS may act as a retrograde signal, regulating the cell response. The network of endoplasmic reticulum and Golgi apparatus is highly altered in salt-acclimated cells. The molecular and subcellular analysis suggests that the unfolded protein response is induced in salt-acclimated cells. Finally, we propose that this mechanism may mediate cell death in salt-acclimated cells.

Learning Probabilistic Features for Robotic Navigation Using Laser Sensors

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N2), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.