A Survey and Analysis of Multi-Robot Coordination

International audienceIn the field of mobile robotics, the study of multi-robot systems (MRSs) has grown significantly in size and importance in recent years. Having made great progress in the development of the basic problems concerning single-robot control, many researchers shifted their focus to the study of multi-robot coordination. This paper presents a systematic survey and analysis of the existing literature on coordination, especially in multiple mobile robot systems (MMRSs). A series of related problems have been reviewed, which include a communication mechanism, a planning strategy and a decision-making structure. A brief conclusion and further research perspectives are given at the end of the paper

Coordination of Multirobot Teams and Groups in Constrained Environments: Models, Abstractions, and Control Policies

Robots can augment and even replace humans in dangerous environments, such as search and rescue and reconnaissance missions, yet robots used in these situations are largely tele-operated. In most cases, the robots\u27 performance depends on the operator\u27s ability to control and coordinate the robots, resulting in increased response time and poor situational awareness, and hindering multirobot cooperation. Many factors impede extended autonomy in these situations, including the unique nature of individual tasks, the number of robots needed, the complexity of coordinating heterogeneous robot teams, and the need to operate safely. These factors can be partly addressed by having many inexpensive robots and by control policies that provide guarantees on convergence and safety. In this thesis, we address the problem of synthesizing control policies for navigating teams of robots in constrained environments while providing guarantees on convergence and safety. The approach is as follows. We first model the configuration space of the group (a space in which the robots cannot violate the constraints) as a set of polytopes. For a group with a common goal configuration, we reduce complexity by constructing a configuration space for an abstracted group state. We then construct a discrete representation of the configuration space, on which we search for a path to the goal. Based on this path, we synthesize feedback controllers, decentralized affine controllers for kinematic systems and nonlinear feedback controllers for dynamical systems, on the polytopes, sequentially composing controllers to drive the system to the goal. We demonstrate the use of this method in urban environments and on groups of dynamical systems such as quadrotors. We reduce the complexity of multirobot coordination by using an informed graph search to simultaneously build the configuration space and find a path in its discrete representation to the goal. Furthermore, by using an abstraction on groups of robots we dissociate complexity from the number of robots in the group. Although the controllers are designed for navigation in known environments, they are indeed more versatile, as we demonstrate in a concluding simulation of six robots in a partially unknown environment with evolving communication links, object manipulation, and stigmergic interactions

Active SLAM: A Review On Last Decade

This article presents a comprehensive review of the Active Simultaneous Localization and Mapping (A-SLAM) research conducted over the past decade. It explores the formulation, applications, and methodologies employed in A-SLAM, particularly in trajectory generation and control-action selection, drawing on concepts from Information Theory (IT) and the Theory of Optimal Experimental Design (TOED). This review includes both qualitative and quantitative analyses of various approaches, deployment scenarios, configurations, path-planning methods, and utility functions within A-SLAM research. Furthermore, this article introduces a novel analysis of Active Collaborative SLAM (AC-SLAM), focusing on collaborative aspects within SLAM systems. It includes a thorough examination of collaborative parameters and approaches, supported by both qualitative and statistical assessments. This study also identifies limitations in the existing literature and suggests potential avenues for future research. This survey serves as a valuable resource for researchers seeking insights into A-SLAM methods and techniques, offering a current overview of A-SLAM formulation.Comment: 34 pages, 8 figures, 6 table

Algoritmo bioinspirado a redes de robots para la asistencia en operaciones de busqueda y rescate

ilustraciones, diagramas, fotografíasThis thesis proposes a bio-inspired algorithm for robot networks assisting in the operations of search and rescue scenarios. We consider ants as social animals to study and abstract beha- viors that can be useful in the framework of search and rescue using robots. We consider three main topics to address when using robots to assist rescuers. First, the exploration and mapping of the disaster zones. For this, we consider the mecha- nisms and interactions of ants to explore their environment, look for food, avoid predators, and explore better places to establish a nest. Then, we deploy robots to explore the en- vironment and discourage robots from entering regions other robots have explored using pheromones as markers for the robots. We also abstract the randomness ants use to explore and implement a Q-learning algorithm that allows robots to explore unvisited regions. Second, the navigation and victim detection. Once the environment has been explored, we vi use Reynolds rules to allow the navigation of robots to create cohesion, attraction to target goals, and repulsion to obstacles and inter-agent collisions. Then, we use a neural network to determine whether what robots are detecting is a victim. Lastly, we use a consensus-like approach to classify victims or no victims based on distributed information. Lastly, ants have been famous for carrying loads that surpass their size and payload capacity by cooperating. We consider quadrotors to carry loads cooperatively that can be medical supplies or victims in search and rescue (Texto tomado de la fuente)Esta tesis propone un algoritmo bioinspirado para redes de robots que asisten en las operaciones de escenarios de busqueda y rescate. Consideramos a las hormigas como animales sociales para estudiar y abstraer comportamientos que pueden ser utiles en el marco de la busqueda y rescate mediante robots. Consideramos tres temas principales para abordar cuando se utilizan robots para ayudar a los rescatistas. Primero, la exploracion y mapeo de las zonas de desastre. Para esto, consideramos los mecanismos e interacciones de las hormigas para explorar su entorno, buscar comida, evitar depredadores y explorar mejores lugares para establecer un nido. Luego, desplegamos robots para explorar el entorno y disuadimos a los robots de ingresar a regiones que otros robots han explorado usando feromonas como marcadores para los robots. Tambien abstraemos la aleatoriedad que usan las hormigas para explorar e implementar un algoritmo Q-learning que permite a los robots explorar regiones no visitadas. En segundo lugar, la navegacion y deteccion de vıctimas. Una vez que se ha explorado el entorno, usamos las reglas de Reynolds para permitir que la navegacion de los robots cree cohesion, atraccion hacia los objetivos y repulsion hacia los obstaculos y las colisiones entre agentes. Luego, usamos una red neuronal para determinar si lo que detectan los robots es una vıctima. Por ultimo, utilizamos un enfoque de consenso para clasificar a las vıctimas o no vıctimas en funcion de la informacion distribuida. Por ultimo, las hormigas han sido famosas por llevar cargas que superan su tamano y capacidad de carga al cooperar. Consideramos quadrotors para transportar cargas de manera cooperativa que pueden ser suministros medicos o vıctimas en busqueda y rescate.MaestríaMagister en Ingenieria - Automatizacion IndustrialRobotic

A Hybrid Multi-Robot Control Architecture

Multi-robot systems provide system redundancy and enhanced capability versus single robot systems. Implementations of these systems are varied, each with specific design approaches geared towards an application domain. Some traditional single robot control architectures have been expanded for multi-robot systems, but these expansions predominantly focus on the addition of communication capabilities. Both design approaches are application specific and limit the generalizability of the system. This work presents a redesign of a common single robot architecture in order to provide a more sophisticated multi-robot system. The single robot architecture chosen for application is the Three Layer Architecture (TLA). The primary strength of TLA is in the ability to perform both reactive and deliberative decision making, enabling the robot to be both sophisticated and perform well in stochastic environments. The redesign of this architecture includes incorporation of the Unified Behavior Framework (UBF) into the controller layer and an addition of a sequencer-like layer (called a Coordinator) to accommodate the multi-robot system. These combine to provide a robust, independent, and taskable individual architecture along with improved cooperation and collaboration capabilities, in turn reducing communication overhead versus many traditional approaches. This multi-robot systems architecture is demonstrated on the RoboCup Soccer Simulator showing its ability to perform well in a dynamic environment where communication constraints are high

Market-Based Approach to Mobile Surveillance Systems

The active surveillance of public and private sites is increasingly becoming a very important and critical issue. It is, therefore, imperative to develop mobile surveillance systems to protect these sites. Modern surveillance systems encompass spatially distributed mobile and static sensors in order to provide effective monitoring of persistent and transient objects and events in a given area of interest (AOI). The realization of the potential of mobile surveillance requires the solution of different challenging problems such as task allocation, mobile sensor deployment, multisensor management, cooperative object detection and tracking, decentralized data fusion, and interoperability and accessibility of system nodes. This paper proposes a market-based approach that can be used to handle different problems of mobile surveillance systems. Task allocation and cooperative target tracking are studied using the proposed approach as two challenging problems of mobile surveillance systems. These challenges are addressed individually and collectively

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future