Flock Identification using Connected Components Labeling for Multi-Robot Shepherding

Shepherding is often used in robotics and applied to various domains such as military in Unmanned Aerial Vehicle (UAV) or Unmanned Ground Vehicle (UGV) combat scenarios, disaster rescue and even in manufacturing. Generally, robot shepherding refers to a task of a robot known as shepherd or sheep herder, who guards and takes care of flocks of sheep, to make sure that the flock is intact and protect them from predators. In order to make an accurate decision, the shepherd needs to identify the flock that needs to be managed. How does the shepherd can precisely identify a group of animals as a flock? How can one actually judge a flock of sheep, is a flock? How does the shepherd decide how to approach or to steer the flock? These are the questions that relates to flock identification. In this paper, a new method using connected components labeling is proposed to cater the problem of flock identification in multi-robot shepherding scenarios. The results shows that it is a feasible approach, and can be used when integrated with the Player/Stage robotics simulation platform

Immune systems inspired multi-robot cooperative shepherding

Certain tasks require multiple robots to cooperate in order to solve them. The main problem with multi-robot systems is that they are inherently complex and usually situated in a dynamic environment. Now, biological immune systems possess a natural distributed control and exhibit real-time adaptivity, properties that are required to solve problems in multi-robot systems. In this thesis, biological immune systems and their response to external elements to maintain an organism's health state are researched. The objective of this research is to propose immune-inspired approaches to cooperation, to establish an adaptive cooperation algorithm, and to determine the refinements that can be applied in relation to cooperation. Two immune-inspired models that are based on the immune network theory are proposed, namely the Immune Network T-cell-regulated---with Memory (INT-M) and the Immune Network T-cell-regulated---Cross-Reactive (INT-X) models. The INT-M model is further studied where the results have suggested that the model is feasible and suitable to be used, especially in the multi-robot cooperative shepherding domain. The Collecting task in the RoboShepherd scenario and the application of the INT-M algorithm for multi-robot cooperation are discussed. This scenario provides a highly dynamic and complex situation that has wide applicability in real-world problems. The underlying 'mechanism of cooperation' in the immune inspired model (INT-M) is verified to be adaptive in this chosen scenario. Several multi-robot cooperative shepherding factors are studied and refinements proposed, notably methods used for Shepherds' Approach, Shepherds' Formation and Steering Points' Distance. This study also recognises the importance of flock identification in relation to cooperative shepherding, and the Connected Components Labelling method to overcome the related problem is presented. Further work is suggested on the proposed INT-X model that was not implemented in this study, since it builds on top of the INT-M algorithm and its refinements. This study can also be extended to include other shepherding behaviours, further investigation of other useful features of biological immune systems, and the application of the proposed models to other cooperative tasks

Adaptive and learning-based formation control of swarm robots

Autonomous aerial and wheeled mobile robots play a major role in tasks such as search and rescue, transportation, monitoring, and inspection. However, these operations are faced with a few open challenges including robust autonomy, and adaptive coordination based on the environment and operating conditions, particularly in swarm robots with limited communication and perception capabilities. Furthermore, the computational complexity increases exponentially with the number of robots in the swarm. This thesis examines two different aspects of the formation control problem. On the one hand, we investigate how formation could be performed by swarm robots with limited communication and perception (e.g., Crazyflie nano quadrotor). On the other hand, we explore human-swarm interaction (HSI) and different shared-control mechanisms between human and swarm robots (e.g., BristleBot) for artistic creation. In particular, we combine bio-inspired (i.e., flocking, foraging) techniques with learning-based control strategies (using artificial neural networks) for adaptive control of multi- robots. We first review how learning-based control and networked dynamical systems can be used to assign distributed and decentralized policies to individual robots such that the desired formation emerges from their collective behavior. We proceed by presenting a novel flocking control for UAV swarm using deep reinforcement learning. We formulate the flocking formation problem as a partially observable Markov decision process (POMDP), and consider a leader-follower configuration, where consensus among all UAVs is used to train a shared control policy, and each UAV performs actions based on the local information it collects. In addition, to avoid collision among UAVs and guarantee flocking and navigation, a reward function is added with the global flocking maintenance, mutual reward, and a collision penalty. We adapt deep deterministic policy gradient (DDPG) with centralized training and decentralized execution to obtain the flocking control policy using actor-critic networks and a global state space matrix. In the context of swarm robotics in arts, we investigate how the formation paradigm can serve as an interaction modality for artists to aesthetically utilize swarms. In particular, we explore particle swarm optimization (PSO) and random walk to control the communication between a team of robots with swarming behavior for musical creation

Hardware dedicado para sistemas empotrados de visión

La constante evolución de las Tecnologías de la Información y las Comunicaciones no solo ha permitido que más de la mitad de la población mundial esté actualmente interconectada a través de Internet, sino que ha sido el caldo de cultivo en el que han surgido nuevos paradigmas, como el ‘Internet de las cosas’ (IoT) o la ‘Inteligencia ambiental’ (AmI), que plantean la necesidad de interconectar objetos con distintas funcionalidades para lograr un entorno digital, sensible y adaptativo, que proporcione servicios de muy distinta índole a sus usuarios. La consecución de este entorno requiere el desarrollo de dispositivos electrónicos de bajo coste que, con tamaño y peso reducido, sean capaces de interactuar con el medio que los rodea, operar con máxima autonomía y proporcionar un elevado nivel de inteligencia. La funcionalidad de muchos de estos dispositivos incluirá la capacidad para adquirir, procesar y transmitir imágenes, extrayendo, interpretando o modificando la información visual que resulte de interés para una determinada aplicación. En el marco de este desafío surge la presente Tesis Doctoral, cuyo eje central es el desarrollo de hardware dedicado para la implementación de algoritmos de procesamiento de imágenes y secuencias de vídeo usados en sistemas empotrados de visión. El trabajo persigue una doble finalidad. Por una parte, la búsqueda de soluciones que, por sus prestaciones y rendimiento, puedan ser incorporadas en sistemas que satisfagan las estrictas exigencias de funcionalidad, tamaño, consumo de energía y velocidad de operación demandadas por las nuevas aplicaciones. Por otra, el diseño de una serie de bloques funcionales implementados como módulos de propiedad intelectual, que permitan aliviar la carga computacional de las unidades de procesado de los sistemas en los que se integren. En la Tesis se proponen soluciones específicas para la implementación de dos tipos de operaciones habitualmente presentes en muchos sistemas de visión artificial: la sustracción de fondo y el etiquetado de componentes conexos. Las distintas alternativas surgen como consecuencia de aplicar una adecuada relación de compromiso entre funcionalidad y coste, entendiendo este último criterio en términos de recursos de cómputo, velocidad de operación y potencia consumida, lo que permite cubrir un amplio espectro de aplicaciones. En algunas de las soluciones propuestas se han utilizado además, técnicas de inferencia basadas en Lógica Difusa con idea de mejorar la calidad de los sistemas de visión resultantes. Para la realización de los diferentes bloques funcionales se ha seguido una metodología de diseño basada en modelos, que ha permitido la realización de todo el ciclo de desarrollo en un único entorno de trabajo. Dicho entorno combina herramientas informáticas que facilitan las etapas de codificación algorítmica, diseño de circuitos, implementación física y verificación funcional y temporal de las distintas alternativas, acelerando con ello todas las fases del flujo de diseño y posibilitando una exploración más eficiente del espacio de posibles soluciones. Asimismo, con el objetivo de demostrar la funcionalidad de las distintas aportaciones de esta Tesis Doctoral, algunas de las soluciones propuestas han sido integradas en sistemas de vídeo reales, que emplean buses estándares de uso común. Los dispositivos seleccionados para llevar a cabo estos demostradores han sido FPGAs y SoPCs de Xilinx, ya que sus excelentes propiedades para el prototipado y la construcción de sistemas que combinan componentes software y hardware, los convierten en candidatos ideales para dar soporte a la implementación de este tipo de sistemas.The continuous evolution of the Information and Communication Technologies (ICT), not only has allowed more than half of the global population to be currently interconnected through Internet, but it has also been the breeding ground for new paradigms such as Internet of Things (ioT) or Ambient Intelligence (AmI). These paradigms expose the need of interconnecting elements with different functionalities in order to achieve a digital, sensitive, adaptive and responsive environment that provides services of distinct nature to the users. The development of low cost devices, with small size, light weight and a high level of autonomy, processing power and ability for interaction is required to obtain this environment. Attending to this last feature, many of these devices will include the capacity to acquire, process and transmit images, extracting, interpreting and modifying the visual information that could be of interest for a certain application. This PhD Thesis, focused on the development of dedicated hardware for the implementation of image and video processing algorithms used in embedded systems, attempts to response to this challenge. The work has a two-fold purpose: on one hand, the search of solutions that, for its performance and properties, could be integrated on systems with strict requirements of functionality, size, power consumption and speed of operation; on the other hand, the design of a set of blocks that, packaged and implemented as IP-modules, allow to alleviate the computational load of the processing units of the systems where they could be integrated. In this Thesis, specific solutions for the implementation of two kinds of usual operations in many computer vision systems are provided. These operations are background subtraction and connected component labelling. Different solutions are created as the result of applying a good performance/cost trade-off (approaching this last criteria in terms of area, speed and consumed power), able to cover a wide range of applications. Inference techniques based on Fuzzy Logic have been applied to some of the proposed solutions in order to improve the quality of the resulting systems. To obtain the mentioned solutions, a model based-design methodology has been applied. This fact has allowed us to carry out all the design flow from a single work environment. That environment combines CAD tools that facilitate the stages of code programming, circuit design, physical implementation and functional and temporal verification of the different algorithms, thus accelerating the overall processes and making it possible to explore the space of solutions. Moreover, aiming to demonstrate the functionality of this PhD Thesis’s contributions, some of the proposed solutions have been integrated on real video systems that employ common and standard buses. The devices selected to perform these demonstrators have been FPGA and SoPCs (manufactured by Xilinx) since, due to their excellent properties for prototyping and creating systems that combine software and hardware components, they are ideal to develop these applications

An Approach Based on Particle Swarm Optimization for Inspection of Spacecraft Hulls by a Swarm of Miniaturized Robots

The remoteness and hazards that are inherent to the operating environments of space infrastructures promote their need for automated robotic inspection. In particular, micrometeoroid and orbital debris impact and structural fatigue are common sources of damage to spacecraft hulls. Vibration sensing has been used to detect structural damage in spacecraft hulls as well as in structural health monitoring practices in industry by deploying static sensors. In this paper, we propose using a swarm of miniaturized vibration-sensing mobile robots realizing a network of mobile sensors. We present a distributed inspection algorithm based on the bio-inspired particle swarm optimization and evolutionary algorithm niching techniques to deliver the task of enumeration and localization of an a priori unknown number of vibration sources on a simplified 2.5D spacecraft surface. Our algorithm is deployed on a swarm of simulated cm-scale wheeled robots. These are guided in their inspection task by sensing vibrations arising from failure points on the surface which are detected by on-board accelerometers. We study three performance metrics: (1) proximity of the localized sources to the ground truth locations, (2) time to localize each source, and (3) time to finish the inspection task given a 75% inspection coverage threshold. We find that our swarm is able to successfully localize the present so

A Strategy for Building Spiritual Resilience in Marines Using the Twenty-Third Psalm

This ministry focus paper develops a strategy for building spiritual resilience in Marines affected by combat and operational stress. It employs a spiritual discipline training seminar designed to build the resilience attributes of contentment, peace, restoration, security, grace, and joy as illustrated in the twenty-third Psalm. The paper argues that Marines who understand and apply six selected spiritual disciplines will experience a measurable decrease in combat stress symptoms and a measurable increase in spiritual resilience. Furthermore, this spiritual resilience will provide a measure of healing from the destructive effects of current combat stress exposure and protect them against the effects of future exposure to combat stress. The thesis was tested on Marines assigned to Kaneohe Bay, Hawaii. Based on resilience research and a thorough examination of Scripture, this paper presents a theology of spiritual resilience with specific focus on the six spiritual resilience attributes of Psalm 23. These attributes have been paired with specific spiritual disciplines selected to develop the attributes based on theological conclusions drawn from this study. The disciplines include Scripture study for building contentment, meditation for developing peace, confession that leads to restoration, prayer that fosters security, service that inspires grace, and celebration that elicits joy. This strategy has employed these disciplines in a two-day seminar that includes pre-seminar and post-seminar assessments in order to analyze the effects of this approach. This paper concludes that the practice of spiritual disciplines reduces the symptoms of combat and operational stress and increases spiritual resilience. However, additional research may be required to determine the long-term effectiveness of this strategy particularly the preventative aspect of this approach for those in combat. Based on this study, the project has potential for wider application beyond the military community to civilian churches, particularly those who offer ministry to former military members and their families. Content Reader: Dr. Jeff Saville, DMi