Robot Map Building from Sonar and Laser Information using DSmT with Discounting Theory

In this paper, a new method of information fusion – DSmT (Dezert and Smarandache Theory) is introduced to apply to managing and dealing with the uncertain information from robot map building. Here we build grid map form sonar sensors and laser range finder (LRF). The uncertainty mainly comes from sonar sensors and LRF. Aiming to the uncertainty in static environment, we propose Classic DSm (DSmC) model for sonar sensors and laser range finder, and construct the general basic belief assignment function (gbbaf) respectively. Generally speaking, the evidence sources are unreliable in physical system, so we must consider the discounting theory before we apply DSmT. At last, Pioneer II mobile robot serves as a simulation experimental platform. We build 3D grid map of belief layout, then mainly compare the effect of building map using DSmT and DST. Through this simulation experiment, it proves that DSmT is very successful and valid, especially in dealing with highly conflicting information. In short, this study not only finds a new method for building map under static environment, but also supplies with a theory foundation for us to further apply Hybrid DSmT (DSmH) to dynamic unknown environment and multi-robots- building map together

Cooperative Acoustic Navigation Scheme for Heterogenous Autonomous Underwater Vehicles

International audienceCooperative Acoustic Navigation Scheme for Heterogenous Autonomous Underwater Vehicle

Endocytic regulation of alkali metal transport proteins in mammals, yeast and plants

The relative concentrations of ions and solutes inside cells are actively maintained by several classes of transport proteins, in many cases against their concentration gradient. These transport processes, which consume a large portion of cellular energy, must be constantly regulated. Many structurally distinct families of channels, carriers, and pumps have been characterized in considerable detail during the past decades and defects in the function of some of these proteins have been linked to a growing list of human diseases. The dynamic regulation of the transport proteins present at the cell surface is vital for both normal cellular function and for the successful adaptation to changing environments. The composition of proteins present at the cell surface is controlled on both the transcriptional and post-translational level. Post-translational regulation involves highly conserved mechanisms of phosphorylation- and ubiquitylation-dependent signal transduction routes used to modify the cohort of receptors and transport proteins present under any given circumstances. In this review, we will summarize what is currently known about one facet of this regulatory process: the endocytic regulation of alkali metal transport proteins. The physiological relevance, major contributors, parallels and missing pieces of the puzzle in mammals, yeast and plants will be discussed.This work was supported by grant BFU2011-30197-C03-03 from the Ministerio de Ciencia e Innovacion (Spain). V.L.-T. is supported by a fellowship from the Universidad Politecnica de Valencia. C. P. is supported by a fellowship from the Consejo Superior de Investigaciones Cientificas (Spain).Mulet Salort, JM.; Llopis Torregrosa, V.; Primo Planta, C.; Marques Romero, MC.; Yenush, L. (2013). 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The Improved SVM Multi Objects's Identification for the Uncalibrated Visual Servoing

For the assembly of multi micro objects in micromanipulation, the first task is to identify multi micro parts. We present an improved support vector machine algorithm, which employs invariant moments based edge extraction to obtain feature attribute and then presents a heuristic attribute reduction algorithm based on rough set's discernibility matrix to obtain attribute reduction, with using support vector machine to identify and classify the targets. The visual servoing is the second task. For avoiding the complicated calibration of intrinsic parameter of camera, We apply an improved broyden's method to estimate the image jacobian matrix online, which employs chebyshev polynomial to construct a cost function to approximate the optimization value, obtaining a fast convergence for online estimation. Last, a two DOF visual controller based fuzzy adaptive PD control law for micro-manipulation is presented. The experiments of micro-assembly of micro parts in microscopes confirm that the proposed methods are effective and feasible

Image Jacobian Matrix Estimation Based on Online Support Vector Regression

Research into robotics visual servoing is an important area in the field of robotics. It has proven difficult to achieve successful results for machine vision and robotics in unstructured environments without using any a priori camera or kinematic models. In uncalibrated visual servoing, image Jacobian matrix estimation methods can be divided into two groups: the online method and the offline method. The offline method is not appropriate for most natural environments. The online method is robust but rough. Moreover, if the images feature configuration changes, it needs to restart the approximating procedure. A novel approach based on an online support vector regression (OL-SVR) algorithm is proposed which overcomes the drawbacks and combines the virtues just mentioned

Target Tracking for Visual Servoing Systems Based on an Adaptive Kalman Filter

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