Trajectory tracking and time delay management of 4-mecanum wheeled mobile robots (4-MWMR)

International audienceNowadays, wheeled mobile robots have a very important role in industrial applications, namely in transportation tasks thanks to their accuracy and rapidity. However, meeting obstacles while executing a mission can cause an important time delay, which is not appreciable in industry where production must be optimal. This paper deals with the time delay management, the trajectory generation and the tracking problem applied on four wheeled omnidirectional mobile robots. A strategy is proposed to minimize or compensate the time delay caused by obstacles. The approach is done by updating the reference trajectory. This update helps to track the trajectory in real time, a new control law based on the feedback linearization control theory is synthesized to track perfectly generated or updated trajectories

Detection & isolation of sensor and actuator additive faults in a 4-mecanum wheeled mobile robot (4-MWMR)

International audienceIn this paper, the fault detection and isolation problem regarding actuation and sensing of a 4-mecanum wheeled mobile robot (4-MWMR) is studied. The challenge with respect to the current state of the art lies in detecting and distinguishing wheel sensor from wheel actuator additive faults for this kind of robots. An approach based on generating residuals is proposed. Sensor faults isolation is based on simply analyzing residual signatures which are different under each sensor fault. Due to omni-move properties, actuator faults are, however, more difficult to be isolated. More residual characteristics must be taken into consideration to achieve the isolation

New approach for gas identification using supervised learning methods (SVM and LVQ)

This article proposes a new approach for gas identification, this approach relies on applying supervised learning methods to identify a single gas as well as a mixture of two gases. The gas is trapped in a gas discharge tube, it is then ionized at a relatively low pressure using an HV transformer. The images captured after the ionization of each single gas is then captured and transformed into a database after being treated in order to be classified. The obtained results were very satisfying for SVM as well as for LVQ. For the case of identification of a single gas, the learning rate as well as the validation rate for both methods were 100%. However, for the case of mixture of two gases, a Multi-Layer Perceptron neural network was used to identify the gases, the learning rate as well as the validation rate were 98.59% and 98.77% respectively. The program developed on MATLAB takes the captured image as an input and outputs the identified gases for the user. The gases used in the experiments are Argon (Ar), oxygen (O2), Helium (He) and carbon dioxide (CO2)

Diagnostic de défauts des robots mobiles à roues, et gestion du retard généré par les obstacles mobiles

Ce travail de thèse s’inscrit dans le cadre du projet européen PRODUCTIVE4.0 en partenariat avec STMicroelectronics de Rousset, France. Afin d’optimiser la production, STMicroelectronics intègre deux types de robots mobiles à roues (les robots unicycles et les robots omnidirectionnels à 4 roues Mecanum) dans la fab (installations de fabrication du semi-conducteur) pour le transport des produits entre les divers équipements de la chaîne de production. Dans le cadre des travaux de cette thèse, nous distinguons deux problématiques majeures pouvant empêcher les robots de bien effectuer leur tâche : l’apparition de défauts au niveau des actionneurs ou des capteurs, et le retard qui peut être généré par les obstacles mobiles et imprévisibles lors de la navigation des robots. Nous nous intéressons dans un premier temps aux robots unicycles. Nous proposons une approche à base d’observateur de Kalman afin de diagnostiquer les défauts actionneurs et capteurs. Une approche basée sur l’estimation et la compensation des défauts permet ensuite de les accommoder. Dans un second temps, nous nous focalisons sur les robots omnidirectionnels et nous proposons des méthodes à base d’observateurs (de Kalman et à entrées inconnues) afin de diagnostiquer les défauts actionneurs et capteurs. Ensuite, l’impact des défauts actionneurs sur le comportement des robots est étudié. Enfin, nous traitons la problématique liée au retard généré par les obstacles en proposant une méthodologie basée sur la reconfiguration des trajectoires de référence afin de compenser ce retardThe work presented in this thesis is a part of the European project PRODUCTIVE4.0 in partnership with STMicroelectronics of Rousset, France. In order to optimize the production, STMicroelectronics integrates two types of wheeled mobile robots (unicycle mobile robots and omnidrectional mobile robots with 4 Mecanum wheels) in the fab (semiconductor manufacturing facility) to transport products between the various equipments in the production chain. In this thesis, we distinguish two major issues that can prevent the robots from well performing their task : the apparition of faults at the actuators or the sensors level, and the delay that can be generated by moving and unpredictable obstacles while navigating. Firstly, we are interested in unicycle robots. We propose a Kalman observer-based approach to diagnose the actuators and sensors faults. Then, an approach based on the faults estimation and compensation allows to accommodate these faults. Secondly, we focus on omnidirectional robots and we propose methods based on observers (Kalman and unknown inputs) in order to diagnose the actuators and sensors faults. After that, the impact of the actuators faults on the robots behavior is studied. Finally, we deal with the problem linked to the obstacles generated delay by proposing a methodology based on the reference trajectories reconfi guration in order to compensate this dela

The removal efficiency and reaction mechanism of the aluminum coagulant on phenolic compounds in the presence of hardness salts

This study is the evaluation of the coagulation efficiency of the aluminum sulfate on the removal of catechol and pyrogallol. The study has focused on the impact of inorganic components of hardness Algerian waters. Jar-test trials were conducted on the two phenolic compounds dissolved in distilled water only, which was later enriched with minerals. Several reaction parameters varied, including the effect of pH and the influence of the salt content, and this approach yielded a better understanding of interaction between phenolic compounds and calcium/magnesium salts. The results indicate that the process efficiency depends on the number and position of OH in molecules. The main mechanisms would be either a physical adsorption, an exchange of ligand, or complexation on the floc surface of aluminum hydroxide. Moreover, the addition of inorganic salts appears to improve removal efficiency of tested phenolic compounds and have an effect on the optimal pH range for coagulation

New approach for gas identification using supervised learning methods (SVM and LVQ)

This article proposes a new approach for gas identification, this approach relies on applying supervised learning methods to identify a single gas as well as a mixture of two gases. The gas is trapped in a gas discharge tube, it is then ionized at a relatively low pressure using an HV transformer. The images captured after the ionization of each single gas is then captured and transformed into a database after being treated in order to be classified. The obtained results were very satisfying for SVM as well as for LVQ. For the case of identification of a single gas, the learning rate as well as the validation rate for both methods were 100%. However, for the case of mixture of two gases, a Multi-Layer Perceptron neural network was used to identify the gases, the learning rate as well as the validation rate were 98.59% and 98.77% respectively. The program developed on MATLAB takes the captured image as an input and outputs the identified gases for the user. The gases used in the experiments are Argon (Ar), oxygen (O2), Helium (He) and carbon dioxide (CO2)

Trajectory reconfiguration for time delay reduction in the case of unexpected obstacles: application to 4-mecanum wheeled mobile robots (4-MWMR) for industrial purposes

International audienceNowadays, wheeled mobile robots have a very important role in industrial applications , namely in transportation tasks thanks to their accuracy and rapidity. However, meeting obstacles while executing a mission can cause an important time delay, which is not appreciable in industry where production must be optimal. This paper proposes a new trajectory reconfiguration approach dealing with obstacle generated time delay, applied on four wheeled omnidirectional mobile robots. A strategy is proposed to compensate or minimize the time delay caused by unexpected obstacles, allowing the robot to respect as well as possible its mission planed duration. This strategy is based on updating the velocity reference profile in real time with respect to the environment changing. The aim is to help the industrial to plan and manage the robot missions, in order to optimize the production

Unicycle and omnidirectional mobile robot fault detection and isolation

International audienc

Unexpected obstacles generated time delay management

International audienc

Detection & isolation of sensor and actuator additive faults in a 4-mecanum wheeled mobile robot (4-MWMR)

International audienceIn this paper, the fault detection and isolation problem regarding actuation and sensing of a 4-mecanum wheeled mobile robot (4-MWMR) is studied. The challenge with respect to the current state of the art lies in detecting and distinguishing wheel sensor from wheel actuator additive faults for this kind of robots. An approach based on generating residuals is proposed. Sensor faults isolation is based on simply analyzing residual signatures which are different under each sensor fault. Due to omni-move properties, actuator faults are, however, more difficult to be isolated. More residual characteristics must be taken into consideration to achieve the isolation