Virtual spring damper method for nonholonomic robotic swarm self-organization and leader following

In this paper, we demonstrate a method for self-organization and leader following of nonholonomic robotic swarm based on spring damper mesh. By self-organization of swarm robots we mean the emergence of order in a swarm as the result of interactions among the single robots. In other words the self-organization of swarm robots mimics some natural behavior of social animals like ants among others. The dynamics of two-wheel robot is derived, and a relation between virtual forces and robot control inputs is defined in order to establish stable swarm formation. Two cases of swarm control are analyzed. In the first case the swarm cohesion is achieved by virtual spring damper mesh connecting nearest neighboring robots without designated leader. In the second case we introduce a swarm leader interacting with nearest and second neighbors allowing the swarm to follow the leader. The paper ends with numeric simulation for performance evaluation of the proposed control method

Planning And Control Of Swarm Motion As Continua

In this thesis, new algorithms for formation control of multi agent systems (MAS) based on continuum mechanics principles will be investigated. For this purpose agents of the MAS are treated as particles in a continuum, evolving in an n-D space, whose desired configuration is required to satisfy an admissible deformation function. Considered is a specific class of mappings that is called homogenous where the Jacobian of the mapping is only a function of time and is not spatially varying. The primary objectives of this thesis are to develop the necessary theory and its validation via simulation on a mobile-agent based swarm test bed that includes two primary tasks: 1) homogenous transformation of MAS and 2) deployment of a random distribution of agents on to a desired configuration. Developed will be a framework based on homogenous transformations for the evolution of a MAS in an n-D space (n=1, 2, and 3), under two scenarios: 1) no inter-agent communication (predefined motion plan); and 2) local inter-agent communication. Additionally, homogenous transformations based on communication protocols will be used to deploy an arbitrary distribution of a MAS on to a desired curve. Homogenous transformation with no communication: A homogenous transformation of a MAS, evolving in an space, under zero inter agent communication is first considered. Here the homogenous mapping, is characterized by an n x n Jacobian matrix ( ) and an n x 1 rigid body displacement vector ( ), that are based on positions of n+1 agents of the MAS, called leader agents. The designed Jacobian ( ) and rigid body displacement vector ( ) are passed onto rest of the agents of the MAS, called followers, who will then use that information to update their positions under a pre- iv defined motion plan. Consequently, the motion of MAS will evolve as a homogenous transformation of the initial configuration without explicit communication among agents. Homogenous Transformation under Local Communication: We develop a framework for homogenous transformation of MAS, evolving in , under a local inter agent communication topology. Here we assume that some agents are the leaders, that are transformed homogenously in an n-D space. In addition, every follower agent of the MAS communicates with some local agents to update its position, in order to grasp the homogenous mapping that is prescribed by the leader agents. We show that some distance ratios that are assigned based on initial formation, if preserved, lead to asymptotic convergence of the initial formation to a final formation under a homogenous mapping. Deployment of a Random Distribution on a Desired Manifold: Deployment of agents of a MAS, moving in a plane, on to a desired curve, is a task that is considered as an application of the proposed approach. In particular, a 2-D MAS evolution problem is considered as two 1-D MAS evolution problems, where x or y coordinates of the position of all agents are modeled as points confined to move on a straight line. Then, for every coordinate of MAS evolution, bulk motion is controlled by two agents considered leaders that move independently, with rest of the follower agents motions evolving through each follower agent communicating with two adjacent agents

Map building, localization and exploration for multi-robot systems

The idea of having robots performing the task for which they have been designed completely autonomously and interacting with the environment has been the main objective since the beginning of mobile robotics. In order to achieve such a degree of autonomy, it is indispensable for the robot to have a map of the environment and to know its location in it, in addition to being able to solve other problems such as motion control and path planning towards its goal. During the fulfillment of certain missions without a prior knowledge of its environment, the robot must use the inaccurate information provided by its on-board sensors to build a map at the same time it is located in it, arising the problem of Simultaneous Localization and Mapping (SLAM) extensively studied in mobile robotics. In recent years, there has been a growing interest in the use of robot teams due to their multiple benefits with respect to single-robot systems such as higher robustness, accuracy, efficiency and the possibility to cooperate to perform a task or to cover larger environments in less time. Robot formations also belongs to this field of cooperative robots, where they have to maintain a predefined structure while navigating in the environment. Despite their advantages, the complexity of autonomous multi-robot systems increases with the number of robots as a consequence of the larger amount of information available that must be handled, stored and transmitted through the communications network. Therefore, the development of these systems presents new difficulties when solving the aforementioned problems which, instead of being addressed individually for each robot, must be solved cooperatively to efficiently exploit all the information collected by the team. The design of algorithms in this multi-robot context should be directed to obtain greater scalability and performance to allow their online execution. This thesis is developed in the field of multi-robot systems and proposes solutions to the navigation, localization, mapping and path planning processes which form an autonomous system. The first part of contributions presented in this thesis is developed in the context of robot formations, which require greater team cooperation and synchronization, although they can be extended to systems without this navigation constraint. We propose localization, map refinement and exploration techniques under the assumption that the formation is provided with a map of the environment, possibly partial and inaccurate, wherein it has to carry out its commanded mission. In a second part, we propose a multi-robot SLAM approach without any assumption about the prior knowledge of a map nor the relationships between robots in which we make use of state of the art methodologies to efficiently manage the resources available in the system. The performance and efficiency of the proposed robot formation and multi-robot SLAM systems have been demonstrated through their implementation and testing both in simulations and with real robots

Formation Navigation and Relative Localisation of Multi-Robot Systems

When proceeding from single to multiple robots, cooperative action is one of the most relevant topics. The domain of robotic security systems contains typical applications for a multi-robot system (MRS). Possible scenarios are safety and security issues on airports, harbours, large industry plants or museums. Additionally, the field of environmental supervision is an up-coming issue. Inherent to these applications is the need for an organised and coordinated navigation of the robots, and a vital prerequisite for any coordinated movements is a good localisation. This dissertation will present novel approaches to the problems of formation navigation and relative localisation with multiple ground-based mobile robots. It also looks into the question what kind of metric is applicable for multi-robot navigation problems. Thereby, the focus of this work will be on aspects of 1. coordinated navigation and movement A new potential-field-based approach to formation navigation is presented. In contradiction to classical potential-field-based formation approaches, the proposed method also uses the orientation between neighbours in the formation. Consequently, each robot has a designated position within the formation. Therefore, the new method is called directed potential field approach. Extensive experiments prove that the method is capable of generating all kinds of formation shapes, even in the presence of dense obstacles. All tests have been conducted with simulated and real robots and successfully guided the robot formation through environments with varying obstacle configurations. In comparison, the nondirected potential field approach turns out to be unstable regarding the positions of the robots within formations. The robots strive to switch their positions, e.g. when passing through narrow passages. Under such conditions the directed approach shows a preferable behaviour, called “breathing”. The formation shrinks or inflates depending on the obstacle situation while trying to maintain its shape and keep the robots at their desired positions inside the formation. For a more particular comparison of formation algorithms it is important to have measures that allow a meaningful evaluation of the experimental data. For this purpose a new formation metric is developed. If there are many obstacles, the formation error must be scaled down to be comparable to an empty environment where the error would be small. Assuming that the environment is unknown and possibly non-static, only actual sensor information can be used for these calculations. We developed a special weighting factor, which is inverse proportional to the “density” of obstacles and which turns out to model the influence of the environment adequately. 2. relative localisation A new method for relative localisation between the members of a robot group is introduced. This relative localisation approach uses mutual sensor observations to localise the robots with respect to other objects – without having an environment model. Techniques like the Extended Kalman Filter (EKF) have proven to be powerful tools in the field of single robot applications. This work presents extensions to these algorithms with respect to the use in MRS. These aspects are investigated and combined under the topic of improving and stabilising the performance of the localisation and navigation process. Most of the common localisation approaches use maps and/or landmarks with the intention of generating a globally consistent world-coordinate system for the robot group. The aim of the here presented relative localisation approach, on the other hand, is to maintain only relative positioning between the robots. The presented method enables a group of mobile robots to start at an unknown location in an unknown environment and then to incrementally estimate their own positions and the relative locations of the other robots using only sensor information. The result is a robust, fast and precise approach, which does not need any preconditions or special assumptions about the environment. To validate the approach extensive tests with both, real and simulated, robots have been conducted. For a more specific evaluation, the Mean Localisation Error (MLE) is introduced. The conducted experiments include a comparison between the proposed Extended Kalman Filter and a standard SLAM-based approach. The developed method robustly delivered an accuracy better than 2 cm and performed at least as well as the SLAM approach. The algorithm coped with scattered groups of robots while moving on arbitrarily shaped paths. In summary, this thesis presents novel approaches to the field of coordinated navigation in multi-robot systems. The results facilitate cooperative movements of robot groups as well as relative localisation among the group members. In addition, a solid foundation for a non-environment related metric for formation navigation is introduced

Multi-robot deployment planning in communication-constrained environments

A lo largo de los últimos años se ha podido observar el aumento del uso de equipos de robots en tareas en las cuales es imposible o poco eficiente la intervención de los humanos, e incluso que implica un cierto grado de riesgo para una persona. Por ejemplo, monitorización de entornos de difícil acceso, como podrían ser túneles, minas, etc. Éste es el tema en el que se ha enfocado el trabajo realizado durante esta tesis: la planificación del despliegue de un equipo de agentes para la monitorización de entornos.La misión de los agentes es alcanzar unas localizaciones de interés y transmitirle la información observada a una estación base estática. Ante la ausencia de una infraestructura de comunicaciones, una transmisión directa a la base es imposible. Por tanto, los agentes se deben coordinar de manera autónoma, de modo que algunos de ellos alcancen los objetivos y otros realicen la función de repetidor para retransmitir la información.Nos hemos centrado en dos líneas de investigación principales, relacionadas con dos maneras del envío de la información a la estación base. En el primer enfoque, los agentes deben mantener un enlace de comunicación con la base en el momento de alcanzar los objetivos. Con el fin de, por ejemplo, poder interactuar desde la base con un robot que ha alcanzado el objetivo. Para ello hemos desarrollado un método que obtiene las posiciones óptimas para los agentes utilizados a modo de repetidor. A continuación, hemos implementado un método de planificación de caminos de modo que los agentes pudiesen navegar el máximo tiempo posible dentro de zonas con señal. Empleando conjuntamente ambos métodos, los agentes extienden el área de cobertura de la estación base, estableciendo un enlace de comunicación desde la misma hasta los objetivos marcados.Utilizando este método, el equipo es capaz de lidiar con variaciones del entorno si la comunicación entre los agentes no se pierde. Sin embargo, los eventos tan comunes e irrelevantes para los seres humanos, como el simple cierre de una puerta, pueden llegar a ser críticos para el equipo de robots. Ya que esto podría interrumpir la comunicación entre el equipo. Por ello, hemos propuesto un método distribuido para que el equipo sea capaz de reconectarse, formando una cadena hacia un objetivo, en escenarios donde haya variaciones con respecto al mapa inicial que poseían los robots.La segunda parte de la presente tesis se ha centrado en misiones de recopilación de datos de un entorno. Aquí la comunicación con la estación base, en el instante de alcanzar un objetivo, no es necesaria y a menudo imposible. Por tanto, en este tipo de escenarios, es más eficiente que algunos agentes, llamados trabajadores, recopilen datos del entorno, y otros, denominados colectores, reúnan la información de los que trabajan para periódicamente retransmitirla a la base. De este modo tan solo los colectores realizan largos viajes a la estación base, mientras que los trabajadores emplean la mayor parte de su tiempo exclusivamente a la recopilación de datos.Primero, hemos desarrollado dos métodos para la planificación de caminos para la sincronización entre los trabajadores y colectores. El primero, muestrea el espacio de manera aleatoria, para obtener una solución lo más rápido posible. El segundo, usando FMM, es más lento, pero obtiene soluciones óptimas.Finalmente, hemos propuesto una técnica global para la misión de recopilación de datos. Este método consiste en: encontrar el mejor balance entre la cantidad de trabajadores y colectores, la mejor división del escenario en áreas de trabajo para los trabajadores, la asociación de los trabajadores para transmitir los datos recopilados a los colectores o directamente a la estación base, así como los caminos de los colectores. El método propuesto trata de encontrar la mejor solución con el fin de entregar la mayor cantidad de datos y que el tiempo de "refresco" de los mismos sea el menor posible.<br /

Cooperative navigation using environment compliant robot formations

Abstract — This paper reports an autonomous cooperative navigation system for robot formations in realistic scenarios. The formation movement control is based on a virtual structure composed by spring-dampers elements, which allows the formation to comply with the environment shape. A different navigation strategy is applied to the leader of the formation and to the rest of robots of the team. The leader plans the trajectories by using a two-level path planner with obstacle avoidance capabilities. The motion of the follower robots is controlled by the virtual structure, which adapts to the environment while the leader is tracked, taking into account the kinodynamic constraints of the vehicles. The system is evaluated in experiments carried out in simulations, some of them made in a realistic and complex urban scenario, and with real robots. I

A Continuum Framework and Homogeneous Map Based Algorithms for Formation Control of Multi Agent Systems

In this dissertation, new algorithms for formation control of multi agent systems (MAS) based on continuum mechanics principles will be suggested. For this purpose, agents of the MAS are considered as particles in a continuum, evolving in R^n, whose desired configuration is required to satisfy an admissible deformation function. Considered is a specific class of mappings that are called homogenous where the Jacobian of the mapping is only a function of time and is not spatially varying. The primary objectives of this dissertation are to develop the necessary theory and its validation on a mobile-agent based swarm test bed that includes two primary tasks: 1) homogenous transformation of MAS and 2) deployment of a random distribution of agents on a desired configuration. Developed will be a framework based on homogenous transformations for the evolution of an MAS in an n-dimensional space (n=1,2, and 3), under1) no inter-agent communication (predefined motion plan), 2) local inter-agent communication, and 3) intelligent perception by agents. In this dissertation, different communication protocols for MAS evolution that are based on certain special features of a homogenous transformation will be developed. It is also aimed to deal with the robustness of tracking of a desired motion by an MAS evolving in R^n. Furthermore, the effect of communication delays in an MAS evolving under consensus algorithms or homogenous maps is investigated. In this regard, the maximum allowable communication delay for MAS evolution is formulated on the basis of eigen-analysis.Ph.D., Mechanical Engineering and Mechanics -- Drexel University, 201