Search

Since about two decades, cellular phones coupled to internet and wireless communications are offering many possibilities that can be exploited by classical telerobotics to free human operators from many constraints providing mobility and ubiquitous applications. This paper presents the design and implementation of an experimental telerobotics system where the human operator supervises and controls remote robots by means of cell phones. To achieve this application, we used Java software namely J2ME platform which is dedicated for programming cell phones and J2SE platform for programming PCs. The adopted software technology of connection between the human operator and the remote robots uses the socket technique with client-server model. The cell phone held by the operator acts as a Client while a PC, situated at the remote robot site, acts as a Server. This application corresponds to Midlet-to-Servlet in Java terminology. Basic simulations and preliminary experiments have been successfully carried out with a three Degrees-of-Freedom (D.O.F) serial robot. These telerobotics systems based on cell phones are effectively offering interesting means to opening new perspectives for mobile and ubiquitous applications.

In this paper we discuss some image processing methods that can be used for motion recognition of human body parts such as hands or arms in order to interact with robots. This interaction is usually associated to gesture-based control. The considered image processing methods have been experienced for feature recognition in applications involving human robot interaction. They are namely: Sequential Similarity Detection Algorithm (SSDA), an appearance-based approach that uses image databases to model objects, and Kanade-Lucas-Tomasi (KLT) algorithm which is usually used for feature tracking. We illustrate the gesture-based interaction by using KLT algorithm. We discuss the adaptation of each of these methods to the context of gesture-based robot interaction and some of their related issues.

Many cells and tissues exhibit chirality that stems from the chirality of proteins and polymers. In the Caenorhabditis elegans zygote, actomyosin contractility drives chiral rotation of the entire cortex circumferentially around the division plane during anaphase. How contractility is translated to cell-scale chirality, and what dictates handedness, are unknown. Septins are candidate contributors to cell-scale chirality because they anchor and cross-link the actomyosin cytoskeleton. We report that septins are required for anaphase cortical rotation. In contrast, the formin CYK-1, which we found to be enriched in the posterior in early anaphase, is not required for cortical rotation but contributes to its chirality. Simultaneous loss of septin and CYK-1 function led to abnormal and often reversed cortical rotation. Our results suggest that anaphase contractility leads to chiral rotation by releasing torsional stress generated during formin-based polymerization, which is polarized along the cell anterior–posterior axis and which accumulates due to actomyosin network connectivity. Our findings shed light on the molecular and physical bases for cellular chirality in the C. elegans zygote. We also identify conditions in which chiral rotation fails but animals are developmentally viable, opening avenues for future work on the relationship between early embryonic cellular chirality and animal body plan.

In this paper we present the direct and inverse analysis of a geometrical model of an UPS manipulator with three degrees of freedom added to a PPP passive central segment. This structure provides a pure translation motion. We will also determine the relations between generalized and articular velocities by using the inverse Jacobian matrix, Further, we determine the reciprocal relations between cartesian and angular velocities of the end effector via articular velocities by direct re-inversion of the Jacobian matrix. This study aims of implementing the control of a parallel robot manipulator. A prototype of a parallel robot has been built up in our laboratory in order to validate the proposed models.

This paper is concerned with the analysis of the tracking capability of Relay Feedback Control Systems (RFCS). The envisioned application is the generation of Pulse-Width-Modulation (PWM) with variable duty-cycle and frequency known also as Duty-Cycle Modulation. In general, two main issues have to be solved with RFCS when used for regulation and tracking. The first issue concerns the determination of autonomous self-oscillations which are generated by the closed loop. The second issue concerns the determination of the relationship between the reference and the output signals. However, if the first issue has beneficiated from different approaches and has been solved particularly in case of zero reference signal, the second issue has got insufficient theoretical results because of mathematical difficulties for obtaining analytical expressions. Considering these reasons, a deep analysis of RFCS constituted of a hysteretic relay and linear systems of first order is presented. Analytical expressions relating self-oscillations and output mean values with respect to the reference signals are obtained. The analysis of these relationships led to infer some conditions under which the relay feedback control can generate commands for regulating and tracking reference signals. It highlights also the key role played by the hysteresis band width for applications based on RFCS. Our analysis, exploiting the analytical expressions, can be used to achieve a complete design for power converters. Moreover, simulation and experiments have confirmed our results.

This paper deals with the predictive capabilities of a NARX-based forecaster used to predict the output power converted with a PV panel in isolated conditions. A time-series based NARX model is proposed and the influence of the meteorological data such as irradiance, ambient temperature and wind speed, and the impact of the training algorithm on the performance of the NARX based forecaster model is studied. The results show that for the studied area, the NARX model trained by three meteorological data as inputs, the output power as output using Bayesian Regularization algorithm gives best performance with a mean squared error of 2.10414e-2.

Some dynamical linear elements including on-off elements such as electro-mechanical relays and electronic components used in switching mode for some feedback control systems can present special features such as the capability to autonomously generate stable self-oscillations. This paper concerns the comparison of two approaches enabling to determine the frequency of self-oscillations in these systems. We examine Tsypkin’s approach which can provide analytical solutions to determining the frequency of existing self-oscillations. On the other hand, we examine the Describing Function (DF) approach which has been developed as an alternative to approximate these solutions. We will compare these two approaches for nonlinear systems of first and second orders. We will examine particularly the possibilities and limits of each approach for calculating the self-oscillations. Simulation of these systems will be performed to visualizes their behaviors. An experimental feedback control system based on electronic circuits used in switching mode has been built as a setup enabling testing and envisioning some applications.

Although living in social groups provides many benefits for group members, such groups also serve as a setting for social competition over rank and influence. Evolutionary accounts suggest that social anxiety plays a role in regulating in-group conflict, as individuals who are concerned about social threat may choose to defer to others to maintain the hierarchical status quo. Here, we examine how social anxiety levels are related to the advice-giving style an individual adopts: a competitive influence-seeking strategy or a defensive blend-in strategy. We begin by demonstrating that similarity to others drives activity in the brain's valuation system, even during a competitive advice-taking task. Then, in three behavioural experiments, we show that social anxiety levels are related to the tendency to give advice resembling the advice given by rival advisers and to refrain from status-seeking behaviour. Social anxiety was also associated with negative social comparisons with rival advisers. Our findings highlight the role of competing social goals in shaping information sharing.

Although living in social groups provides many benefits for group members, such groups also serve as a setting for social competition over rank and influence. Evolutionary accounts suggest that social anxiety plays a role in regulating in-group conflict, as individuals who are concerned about social threat may choose to defer to others to maintain the hierarchical status quo. Here, we examine how social anxiety levels are related to the advice-giving style an individual adopts: a competitive influence-seeking strategy or a defensive blend-in strategy. We begin by demonstrating that similarity to others drives activity in the brain's valuation system, even during a competitive advice-taking task. Then, in three behavioural experiments, we show that social anxiety levels are related to the tendency to give advice resembling the advice given by rival advisers and to refrain from status-seeking behaviour. Social anxiety was also associated with negative social comparisons with rival advisers. Our findings highlight the role of competing social goals in shaping information sharing.

Many cells and tissues exhibit chirality that stems from the chirality of constituent proteins and polymers. For example, the C. elegans zygote undergoes an actomyosin-driven chiral rotation in which the entire cortex is displaced circumferentially around the division plane during anaphase. This phenomenon thus relates to how force and chirality are translated across scales. Although it is known that actomyosin contractility drives this rotation, the molecular mechanisms transmitting contractility to chiral movement, and dictating handedness, are not understood. Septins are candidates for contributing to cell-scale chirality due to their ability to anchor and organize the actomyosin cytoskeleton. Here, we report that septins are required for anaphase cortical rotation. In contrast, the formin CYK-1, which we found to be enriched in the posterior in early anaphase, is not required for cortical rotation, but contributes to its chirality. Simultaneous loss of septin and CYK-1 function led to highly abnormal and often reversed cortical rotation. We propose a model by which anaphase cortical contractility is biased in a chiral fashion via interaction between the circumferential cytokinetic ring and perpendicular, longitudinal formin-based actin bundles that have accumulated torsional stress during formin-based polymerization. Our findings thus shed light on the molecular and physical bases for cellular chirality in the C. elegans zygote. We also identify conditions in which chiral rotation fails but animals are developmentally viable, opening avenues for future work on the relationship between early embryonic cellular chirality and animal body plan.

Interaction and command modes as well as their combination are essential features of modern and futuristic robotic systems interacting with human beings in various dynamical environments. This paper presents a synthetic overview concerning the most command modes used in Human-Robot Interaction Systems (HRIS). It includes the first historical command modes which are namely tele-manipulation, off-line robot programming, and traditional elementary teaching by demonstration. It then introduces the most recent command modes which have been fostered later on by the use of artificial intelligence techniques implemented on more powerful computers. In this context, we will consider specifically the following modes: interactive programming based on the graphical-user-interfaces, voice-based, pointing-on-image-based, gesture-based, and finally brain-based commands. info:eu-repo/semantics/publishedVersion

This paper assesses the optimal farmland that can be irrigated by a predetermined renewable energy system. The optimal irrigated surface from an agriculture area, cultivated by potatoes and tomatoes and powered by a PV system is studied. Two scenarios are discussed: the constraints applied to the first scenario is the limited surface of the agricultural area. While in the second scenario, the surface cultivated with tomatoes must be at least ¼ the surface cultivated with potatoes. Linear programming based on the Simplex algorithm is used to solve the optimization problem. The obtained results show that for the specified cultivating area, and for 10 panels at hand, an optimal surface of about 5.6 ha and 4.7 ha for the first scenario and the second scenario, respectively can be satisfied.

Modeling the estimation of cumulated methane production generated from batch anaerobic bioreactors is of paramount importance. In this context, there are two main modeling approaches. The first approach is based on developing mathematical expressions representing the processes involved in the bioreactors. The AM1 model is known as the most complete one. However, it is a complicated model as it requires about 80 parameters to be tuned. A model named AM2 which is a simplified version of AM1 has also been developed. It is based on only two microbial growth processes and requires only 13 parameters. Nevertheless, both AM1 and AM2 models do not provide explicit mathematical expressions that enable to estimate the temporal evolution of methane production with respect to the parameters involved in the considered models. These models are much more useful for simulations and graphical visualizations of the dynamical behavior of the state variables including methane production. On the other hand, the second approach suggests semi-empirical or data-driven models which are based on simple explicit mathematical expressions that provide an estimate of the cumulated methane production (Logistic model, Gompertz model, etc.). But, this type of models require the identification of few parameters which are extracted from experimental data. Usually, they are simplistic and use only one growth process and thus cannot exhibit the influence of the many parameters involved in such complex dynamic biotechnological systems. In this paper, to overcome the complexity of the first type of models and to avoid the dependency on experimental data in the second type; an explicit analytical mathematical expression is proposed for estimating the cumulated methane production for batch anaerobic bioreactors. This analytical expression is derived via the adoption of some appropriate approximations performed on the set of differential equations characterizing the AM2 model. Therefore, the proposed analytical expression can be considered as an approximation of the AM2 model itself and this is the first contribution of this paper. Graphical profiles of the cumulated methane production are presented showing that of the proposed logistic expression and that of the AM2 model considered as a reference. To the best of the author’s knowledge, no such approach and result have been encountered in the literature. On the other hand, this expression resembles formally to the semi-empiric logistic model. However, the equivalent parameters of the proposed expression as self-defined by the parameters of the AM2 model and do not require experimental data to be identified as it is for the semi-empiric logistic model. Moreover, by comparing the proposed logistic model to the semi-empiric logistic model, an identification of the parameters of the semi-empiric model is linked to the parameters of the AM2 model, providing more insight into the methane production. This can be considered as a second contribution of this paper.

Continuum robots are kinematically redundant and their dynamic models are highly nonlinear. This study aims to overcome this difficulty by presenting a more practical dynamic model of a certain class of continuum robots called cable-driven continuum robot (CDCR). Firstly, the structural design of a CDCR with two rotational degrees of freedom (DOF) is introduced. Then, the kinematic models are derived according to the constant curvature assumption. Considering the complexity of the kinetic energy expression, it has been approximated by the well-known Taylor expansions. This case corresponds to weak bending angles within the specified bending angle range of the robot. On the other hand, due to the low weight of the CDCR components, the gravitational energy effects can be neglected compared to those stemmed from the elastic energy. Thereafter, the corresponding dynamic model is established using Euler-Lagrange method. Static and dynamic models have been illustrated by examples. This analysis and dynamic model development have been compared with the existing scientific literature. The obtained results shown that the consistency and the efficiency of accuracy for real-time have been carried out. However, the dynamic modeling of CDCR with more than 2-DOF leads to a more complex mathematical expression, and cannot be simplified by adopting the similar assumptions and methodology used in the case of 2-DOF.

In this chapter, we present an overview of the state of the art concerning the OER in Morocco, throughout some milestones that we consider to be the most significant. After putting into perspective the political and strategic aspects adopted to lead the Moroccan education system toward a more open pedagogy, we present the main achievements concerning infrastructures and aiming at the generalization of access to resources. We then present some key achievements both at school and university level.

Photovoltaic energy is volatile in nature since it depends on weather conditions. It is important to have an idea about the reliability and the economic feasibility of any new project to decide whether it is right to proceed with the installation of such a project. Hence, it is becoming fundamental to know renewable energy state and production that can be combined with other less variable and more predictable sources to justify the choice of regions for the new photovoltaic projects installation. The current research investigates the forecasting abilities of a NARX based approach. The influence of the meteorological data, such as irradiance, ambient temperature, and wind speed, and the impact of training algorithms on the performance of the NARX-based forecaster is studied. For this purpose, four models are discussed, each model is trained based on three training algorithms. The NARX model using a Bayesian Regularization algorithm, trained by the three meteorological data as inputs and the converted power output as output, outperforms the other models. It consists of a simple architecture with one input layer, a hidden layer containing 1O neurons, and an output layer, with a mean square error of 0.0085 W2 for the training phase and 0.0043 W2 testing phase, and the overall regression of 95.48%. This simplified architecture and low values of the mean square error and the regression coefficient suggest that they are promising photovoltaic output prediction tools, particularly in locations where few meteorological parameters are monitored.

The wind power is well adapted nowadays as solution to the production of electricity or for mechanical use. But wind is a very fluctuating source of energy; it generates a non-permanent and variable power to the loads. This paper presents a strategy to improve the quality of the electric power produced by a wind turbine under variable speed. The mathematical modeling of the various elements of the conversion system is performed. Two control strategies are developed to improve the quality of the energy produced by the wind turbine. The first consists to a judicious management of the DC bus and the second to control the inverters with a corrective proportional resonant. The results obtained after implementation and simulation under Matlab/Simulink platform are presented.Keywords: wind turbine; electric power quality; corrective proportional resonant; DC Bus

International audience; This paper discusses a comparison study of the use of 100% renewable energy systems for desert and remote areas, investigating both a central unique unit and distributed units. An initial HRES consisting of a photovoltaic (PV) array and wind generator is used to power an agricultural area of 4 ha once with a central unit and then with four distributed units. The selection of the optimal size is accomplished through linear programming based on the simplex algorithm to minimize the total life cycle cost. The results show for the first time that the use of a distributed renewable energy system containing a full PV array is cost-effective compared to a central unit.

Hostile environments such as nuclear sites are difficult for men to perform tasks safely. The objective of our work is to construct and test an experimental system of teleoperation oriented to the pick-and-place tasks, using Internet. Two PCs are used, one at the local site and the second at the remote site. The interconnection between these sites is based on the TCP/IP sockets. In the remote site; a webcam sends images manipulator arm through Internet to the control site where a human operator remotely monitors this robot in order to achieve pick-and-place tasks. The camera is horizontally and vertically adjustable. The robot and camera are both controlled remotely via the Internet. A human-centered design has been used to build up the graphical user interface. The task supervision is performed from a local site through an Internet interconnection TCP/IP protocol. The software is mainly written in Java while some low level functions are written with C. Some experiments were successfully realized in local area network, and remotely at a large distance via Internet. The obtained results encouraged us to test other control modes with our system as, mouse-click command, Image-Based Commands and Gesture commands. Therefore, the system can then be used and adapted for various industrial and medical applications. DOI: http://dx.doi.org/10.5755/j01.mech.24.4.19386