A Multi-robot System Coordination Design and Analysis on Wall Follower Robot Group

In this research, multi-robot formation can be established according to the environment or workspace. Group of robots will move sequently if there is no space for robots to stand side by side. Leader robot will be on the front of all robots and follow the right wall. On the other hand, robots will move side by side if there is a large space between them. Leader robot will be tracked the wall on its right side and follow on it while every follower moves side by side. The leader robot have to broadcast the information to all robots in the group in radius 9 meters. Nevertheless, every robot should be received information from leader robot to define their movements in the area. The error provided by fuzzy output process which is caused by read data from ultrasound sensor will drive to more time process. More sampling can reduce the error but it will drive more execution time. Furthermore, coordination time will need longer time and delay. Formation will not be establisehed if packet error happened in the communication process because robot will execute wrong command

Virtual Structure Based Formation Tracking of Multiple Wheeled Mobile Robots: An Optimization Perspective

Today, with the increasing development of science and technology, many systems need to be optimized to find the optimal solution of the system. this kind of problem is also called optimization problem. Especially in the formation problem of multi-wheeled mobile robots, the optimization algorithm can help us to find the optimal solution of the formation problem. In this paper, the formation problem of multi-wheeled mobile robots is studied from the point of view of optimization. In order to reduce the complexity of the formation problem, we first put the robots with the same requirements into a group. Then, by using the virtual structure method, the formation problem is reduced to a virtual WMR trajectory tracking problem with placeholders, which describes the expected position of each WMR formation. By using placeholders, you can get the desired track for each WMR. In addition, in order to avoid the collision between multiple WMR in the group, we add an attraction to the trajectory tracking method. Because MWMR in the same team have different attractions, collisions can be easily avoided. Through simulation analysis, it is proved that the optimization model is reasonable and correct. In the last part, the limitations of this model and corresponding suggestions are given

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Formation morphing and collision avoidance in swarms of robots

Formation maintenance and collision avoidance are two of the key factors in swarm robotics. The demand for autonomous fleets of robots is ever increasing from manufacturing to product deliveries to surveillance to mapping and so on. Moreover, for resource constrained autonomous robots, such as UAVs and UGVs, energy-efficiency is very vital due to their limited batteries. Therefore formation maintenance and collision avoidance developed for such robots need to be energy-efficient. Integration between these two approaches needs to be performed systematically. The experimental analysis of the proposed approaches presented in this thesis target two main branches: 1) action based and 2) perception based energy consumption in a swarm of robots. In the first branch, there are two different paths: i) optimal formation morphing: the main goal is to the optimize the reformation process from the highest level of agitation of the swarm, i.e., maximum disturbance in the formation shape and ii) congestion minimization: the main goal here is to find an optimal solution for distribution of the swarm into sub-swarms to minimize the delays due to over population of the agents while bypassing the obstacles. In the second branch, i.e., perception based energy consumption, the main goal is to increase the mission life on a single charge by injecting the adaptive consciousness into the agents so they can turn off their ranging sensors and navigate while listening to their leader. For formation collision co-awareness, we systematically integrated the methodologies by designing a multi-priority control and utilized the non-rigid mapping scheme of thin-plate splines technique to minimize the deformation caused by obstacle avoidance. For congestion-aware morphing and avoidance maneuvers, we discuss how the delays caused by over population can be minimized with local sense and avoid approach. The leader, upon detection of obstacles, pre-estimates the optimal configuration, i.e., number of agents in the sub-swarms, and divides the swarm as such. We show the efficiency of the proposed approach experimentally

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Swarm Robotics

Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties

Design of a strategy to obtain safe paths from collaborative robot teamwork

Documento en PDF a color.figuras, tablasThis doctoral thesis was designed and implemented using a strategy of explorer agents and a management and monitoring system to obtain the shortest and safest paths. The strategy was simulated using Matlab R2016 in 10 test environments. The comparisons were made between the results obtained by considering each robot's work and contrasting it with the results obtained by implementing the cooperative-collaborative strategy. For this purpose, were used two path planning algorithms, they are the A* and the Greedy Best First Search (GBFS). Some changes were made to these classic algorithms to improve their performance to guarantee interactions and comparisons between them, transforming them into Incremental Heuristic (IH) algorithms, which gave rise to a couple of agents with new path planners called IH-A* and IH-GBFS. The cooperative strategy was implemented with IH-A* and IH-GBFS algorithms to obtain the shortest paths. The cooperative process was used 300 times in 100 complete tests (3 times in 10 tests in each of 10 environments), which allowed determining that the strategy decreased the original path (without cooperation) in 79% of the cases. In 20.50% of cases, the author identified that the cooperative process, reduced to less than half the original path. The collaborative strategy was implemented to obtain the safer path, using a communications system that allows the interaction among the explorer agents, the test environment, and the management and monitoring system to generate early warnings and compare the risk between paths. In this work, the risk is due to hidden marks found by the explorer agents; for this reason, it is implemented a potential risk function that allows obtaining the path risk estimated. The path risk estimated metric is the one that facilitates the evaluation and comparison of risk between paths to find safer paths. The AWMRs operates using a kinematic model, a controller, a path planner, and sensors that allow them to navigate through the environment gently and safely. Simultaneously with the explorer agents, the administration and monitoring system as a user interface that facilitates the presentation and consolidation of results were implemented. Subsequently, 16 tests were carried out, implementing the complete cooperative-collaborative strategy in four different environments, which had hidden marks. When analyzing the results, it was determined that the Shortest Safest Estimated Path was found in 62.5% of the tests. A WMR and a square test stage were built. In the test scenario, 240 path tracking tests were carried out (the WMR travelled 24 different paths; the WMR travelled each path ten times). The path data were obtained using odometry with encoders onboard the robot and image processing through an external camera. The author apply a tracking error analysis on the WMR path, travelling a circumference of 3.64 m in length. When comparing the path obtained with the WMR kinematic model with the data obtained using image processing, a Mean Absolute Percentage Error (MAPE) of 2,807% was obtained; and with the odometry data, the MAPE was 1,224%. As a general conclusion, this study has numerically identified the relevance of the implementation of the cooperative-collaborative strategy in robotic teamwork to find shortest and safest paths, a strategy applied in test environments that have obstacles and hidden marks. The cooperative-collaborative strategy can be used in different applications that involve displacement in a dangerous place or environment, such as a minefield or a region at risk of spreading COVID-19.Esta tesis doctoral fue diseñada e implementada utilizando una estrategia de agentes exploradores y un sistema de gestión y seguimiento para obtener caminos más cortos y seguros. La estrategia se simuló utilizando Matlab R2016 en 10 entornos de prueba. Las comparaciones se realizaron entre los resultados obtenidos al considerar el trabajo realizado por cada robot y contrastarlo con los resultados obtenidos al implementar la estrategia cooperativa-colaborativa. Para ello, se utilizaron dos algoritmos de planificación de rutas, que son el A* y el Greedy Best First Search (GBFS). Se realizaron algunos cambios a estos algoritmos clásicos para mejorar su rendimiento para garantizar interacciones y comparaciones entre ellos, transformándolos en algoritmos Heurísticos Incrementales (IH), lo que dio lugar a un par de agentes con nuevos planificadores de rutas denominados IH-A * e IH- GBFS. La estrategia cooperativa se implementó con algoritmos IH-A * e IH-GBFS para obtener los caminos más cortos. El proceso cooperativo se utilizó 300 veces en 100 pruebas completas (3 veces en 10 pruebas en cada uno de los 10 entornos), lo que permitió determinar que la estrategia disminuyó la trayectoria original (sin cooperación) en el 79% de los casos. En el 20,50% de los casos, el autor identificó que el proceso cooperativo, redujo la distancia entre inicio y meta a menos de la mitad del recorrido original. La estrategia colaborativa se implementó para obtener el camino más seguro, utilizando un sistema de comunicaciones que permite la interacción entre los agentes exploradores, el entorno de prueba y el sistema de gestión y monitoreo para generar alertas tempranas y comparar el riesgo entre caminos. En este trabajo, el riesgo se debe a las marcas ocultas encontradas por los agentes exploradores; por ello, se implementa una función de riesgo potencial que permite obtener el riesgo de ruta estimado. La métrica estimada de riesgo de ruta es la que facilita la evaluación y comparación de riesgo entre rutas para encontrar rutas más seguras. Los robots autónomos móviles con ruedas (en inglés AWMR) operan utilizando un modelo cinemático, un controlador, un planificador de rutas y sensores que les permiten navegar por el entorno de manera suave y segura. Simultáneamente con los agentes exploradores, el autor implementó un sistema de administración y monitoreo como interfaz de usuario que facilita la presentación y consolidación de resultados. Posteriormente, se realizaron 16 pruebas, implementando la estrategia cooperativa-colaborativa completa en cuatro entornos diferentes, que tenían marcas ocultas. Al analizar los resultados, se determinó que una ruta estimada más corta y más segura se obtenía en el 62.5% de las pruebas. Se construyeron un WMR y un escenario de prueba cuadrado. En el escenario de prueba, se llevaron a cabo 240 pruebas de seguimiento de ruta (el WMR recorrió 24 rutas diferentes; el WMR recorrió cada ruta diez veces). Los datos de la trayectoria se obtuvieron utilizando odometría con encoders a bordo del robot y procesamiento de imágenes a través de una cámara externa. El autor aplica un análisis de error de seguimiento en la ruta recorrida por el WMR, generando una circunferencia de 3,64 m de longitud. Al comparar la ruta obtenida con el modelo cinemático del WMR con los datos obtenidos usando el procesamiento de imágenesse obtuvo un error de porcentaje absoluto medio (MAPE) de 2.807%; y con los datos de odometría, el MAPE fue de 1,224%. Como conclusión general, este estudio ha identificado numéricamente la relevancia de la implementación de la estrategia cooperativa-colaborativa en el trabajo en equipo robótico para encontrar caminos más cortos y seguros, estrategia aplicada en entornos de prueba que poseen obstáculos y marcas ocultas. La estrategia cooperativa-colaborativa puede ser utilizada en diferentes aplicaciones que involucran el desplazamiento en un lugar o entorno peligroso, como pueden ser un campo minado o una región en riesgo de propagación de COVID-19.DoctoradoDoctor en Ingeniería - Ingeniería Automátic

Réduction du comportement myope dans le contrôle des FMS : une approche semi-hétérarchique basée sur la simulation-optimisation

Heterarchical-based control for flexible manufacturing systems (FMS) localizes control capabilities in decisional entities (DE), resulting in highly reactive and low complex control architectures. However, these architectures present myopic behavior since DEs have limited visibility of other DEs and their behavior, making difficult to ensure certain global performance. This dissertation focuses on reducing myopic behavior. At first, a definition and a typology of myopic behavior in FMS is proposed. In this thesis, myopic behavior is dealt explicitly so global performance can be improved. Thus, we propose a semi-heterarchical architecture in which a global decisional entity (GDE) deals with different kinds of myopic decisions using simulation-based optimization (SbOs). Different optimization techniques can be used so myopic decisions can be dealt individually, favoring GDE modularity. Then, the SbOs can adopt different roles, being possible to reduce myopic behavior in different ways. More, it is also possible to grant local decisional entities with different autonomy levels by applying different interaction modes. In order to balance reactivity and global performance, our approach accepts configurations in which some myopic behaviors are reduced and others are accepted. Our approach was instantiated to control the assembly cell at Valenciennes AIPPRIMECA center. Simulation results showed that the proposed architecture reduces myopic behavior whereby it strikes a balance between reactivity and global performance. The real implementation on the assembly cell verified the effectiveness of our approach under realistic dynamic scenarios, and promising results were obtained.Le contrôle hétérarchique des systèmes de production flexibles (FMS) préconise un contrôle peu complexe et hautement réactif supporté par des entités décisionnelles locales (DEs). En dépit d'avancées prometteuses, ces architectures présentent un comportement myope car les DEs ont une visibilité informationnelle limitée sue les autres DEs, ce qui rend difficile la garantie d'une performance globale minimum. Cette thèse se concentre sur les approches permettant de réduire cette myopie. D'abord, une définition et une typologie de cette myopie dans les FMS sont proposées. Ensuite, nous proposons de traiter explicitement le comportement myope avec une architecture semi-hétérarchique. Dans celle-ci, une entité décisionnelle globale (GDE) traite différents types de décisions myopes à l'aide des différentes techniques d'optimisation basée sur la simulation (SbO). De plus, les SbO peuvent adopter plusieurs rôles, permettant de réduire le comportement myope de plusieurs façons. Il est également possible d'avoir plusieurs niveaux d'autonomie en appliquant différents modes d'interaction. Ainsi, notre approche accepte des configurations dans lesquelles certains comportements myopes sont réduits et d'autres sont acceptés. Notre approche a été instanciée pour contrôler la cellule flexible AIP- PRIMECA de l'Université de Valenciennes. Les résultats des simulations ont montré que l'architecture proposée peut réduire les comportements myopes en établissant un équilibre entre la réactivité et la performance globale. Des expérimentations réelles ont été réalisées sur la cellule AIP-PRIMECA pour des scenarios dynamiques et des résultats prometteurs ont été obtenus

Path planning for first responders in the presence of moving obstacles

Navigation services have gained much importance for all kinds of human activities ranging from tourist navigation to support of rescue teams in disaster management. However, despite the considerable amount of route guidance research that has been performed, many issues that are related to navigation for first responders still need to be addressed. During disasters, emergencies can result in different types of moving obstacles (e.g., fires, plumes, floods), which make some parts of the road network temporarily unavailable. After such incidents occur, responders have to go to different destinations to perform their tasks in the environment affected by the disaster. Therefore they need a path planner that is capable of dealing with such moving obstacles, as well as generating and coordinating their routes quickly and efficiently. During the past decades, more and more hazard simulations, which can modify the models with incorporation of dynamic data from the field, have been developed. These hazard simulations use methods such as data assimilation, stochastic estimation, and adaptive measurement techniques, and are able to generate more reliable results of hazards. This would allow the hazard simulation models to provide valuable information regarding the state of road networks affected by hazards, which supports path planning for first responders among the moving obstacles. The objective of this research is to develop an integrated navigation system for first responders in the presence of moving obstacles. Such system should be able to navigate one or more responders to one or multiple destinations avoiding the moving obstacles, using the predicted information of the moving obstacles generated from by hazard simulations. In this dissertation, the objective we have is expressed as the following research question: How do we safely and efficiently navigate one or more first responders to one or more destinations avoiding moving obstacles? To address the above research questions, this research has been conducted using the following outline: 1). literature review; 2). conceptual design and analysis; 3). implementation of the prototype; and 4). assessment of the prototype and adaption. We investigated previous research related to navigation in disasters, and designed an integrated navigation system architecture, assisting responders in spatial data storage, processing and analysis.Within this architecture, we employ hazard models to provide the predicted information about the obstacles, and select a geo-database to store the data needed for emergency navigation. Throughout the development of the prototype navigation system, we have proposed: a taxonomy of navigation among obstacles, which categorizes navigation cases on basis of type and multiplicity of first responders, destinations, and obstacles; a multi-agent system, which supports information collection from hazard simulations, spatio-temporal data processing and analysis, connection with a geo-database, and route generation in dynamic environments affected by disasters; data models, which structure the information required for finding paths among moving obstacles, capturing both static information, such as the type of the response team, the topology of the road network, and dynamic information, such as changing availabilities of roads during disasters, the uncertainty of the moving obstacles generated from hazard simulations, and the position of the vehicle; path planning algorithms, which generate routes for one or more responders in the presence of moving obstacles. Using the speed of vehicles, departure time, and the predicted information about the state of the road network, etc., three versions (I, II, and III) of Moving Obstacle Avoiding A* (MOAAStar) algorithms are developed: 1). MOAAstar– I/Non-waiting, which supports path planning in the case of forest fires; 2). MOAAstar–II/Waiting, which introduces waiting options to avoid moving obstacles like plumes; 3). MOAAstar–III/Uncertainty, which can handle the uncertainty in predictions of moving obstacles and incorporate the profile of responders into the routing. We have applied the developed prototype navigation system to different navigation cases with moving obstacles. The main conclusions drawn from our applications are summarized as follows: In the proposed taxonomy, we have identified 16 navigation cases that could occur in disaster response and need to be investigated. In addressing these navigation problems, it would be quite useful to employ computer simulations and models, which can make reliable predicted information about responders, the targets, and obstacles, in finding safe routes for the responders. The approach we provide is general and not limited to the cases of plumes and fires. In our data model, the data about the movement of hazards is represented as moving polygons. This allows the data model to be easily adjusted to merge and organize information from models of different types of disasters. For example, the areas that are affected by floods can also be represented as moving polygons. To facilitate the route calculation, not only the data of obstacles but also the information about the state of road networks affected by obstacles need to be structured and stored in the database. In planning routes for responders, the routing algorithms should incorporate the dynamic data of obstacles to be able to avoid the hazards. Besides, other factors, such as the operation time of tasks, the required arrival time, and departure time, also need to be considered to achieve the objectives in a rescue process, e.g., to minimize the delays caused by the moving obstacles. The profile of responders is quite important for generation of feasible routes for a specific disaster situation. The responders may have different protective equipment that allows them to pass through different types of moving obstacles, and thus can have different classification of risk levels to define the state of the road network. By taking into account the profile of the responders, the navigation system can propose customized and safe routes to them, which would facilitate their disaster response processes. On the basis of our findings, we suggest the following topics for future work: As presented Wang and Zlatanova (2013c), there are still a couple of navigation cases that need to be addressed, especially the ones that involve dynamic destinations. More algorithms would be needed to solve these navigation problems. Besides, some extreme cases (e.g., the obstacle covers the target point during the course of an incident) also need to be investigated. Using standard Web services, an Android navigation application, which can provide navigation services in the environment affected by hazards, needs to be developed and tested in both the daily practice and real disasters. In this application, a user interface with various styling options should also be designed for different situations, e.g., waiting and moving, day and night, and urgent and non-urgent. Because the communication infrastructure may not be available or work properly during a disaster response, a decentralized method is needed to allow different users to negotiate with each other and to make local agreements on the distribution of tasks in case there is no support from the central planning system. Another type of multi-agent system would be needed to handle this situation. Introduce variable traveling speed into the re-routing process. The vehicle speed plays an important role in generation of routes avoiding moving obstacle, and can be influenced by many factors, such as the obstacles, the type of vehicles, traffic conditions, and the type of roads. Therefore, it would be needed to investigate how to derive the current and future speed from trajectories of vehicles. Apply the system to aid navigation in various types of natural disasters, using different hazard simulation models (e.g., flood model). More types of agents would be needed and integrated into the system to handle heterogeneous data from these models. Extensions of the data model are also required to meet a wider range of informational needs when multiple disasters occur simultaneously

Compliant control of Uni/ Multi- robotic arms with dynamical systems

Accomplishment of many interactive tasks hinges on the compliance of humans. Humans demonstrate an impressive capability of complying their behavior and more particularly their motions with the environment in everyday life. In humans, compliance emerges from different facets. For example, many daily activities involve reaching for grabbing tasks, where compliance appears in a form of coordination. Humans comply their handsâ motions with each other and with that of the object not only to establish a stable contact and to control the impact force but also to overcome sensorimotor imprecisions. Even though compliance has been studied from different aspects in humans, it is primarily related to impedance control in robotics. In this thesis, we leverage the properties of autonomous dynamical systems (DS) for immediate re-planning and introduce active complaint motion generators for controlling robots in three different scenarios, where compliance does not necessarily mean impedance and hence it is not directly related to control in the force/velocity domain. In the first part of the thesis, we propose an active compliant strategy for catching objects in flight, which is less sensitive to the timely control of the interception. The soft catching strategy consists in having the robot following the object for a short period of time. This leaves more time for the fingers to close on the object at the interception and offers more robustness than a âhardâ catching method in which the hand waits for the object at the chosen interception point. We show theoretically that the resulting DS will intercept the object at the intercept point, at the right time with the desired velocity direction. Stability and convergence of the approach are assessed through Lyapunov stability theory. In the second part, we propose a unified compliant control architecture for coordinately reaching for grabbing a moving object by a multi-arm robotic system. Due to the complexity of the task and of the system, each arm complies not only with the objectâs motion but also with the motion of other arms, in both task and joint spaces. At the task-space level, we propose a unified dynamical system that endows the multi-arm system with both synchronous and asynchronous behaviors and with the capability of smoothly transitioning between the two modes. At the joint space level, the compliance between the arms is achieved by introducing a centralized inverse kinematics (IK) solver under self-collision avoidance constraints; formulated as a quadratic programming problem (QP) and solved in real-time. In the last part, we propose a compliant dynamical system for stably transitioning from free motions to contacts. In this part, by modulating the robot's velocity in three regions, we show theoretically and empirically that the robot can (I) stably touch the contact surface (II) at a desired location, and (III) leave the surface or stop on the surface at a desired point