Cooperation in Swarms of Robots without Communication

Swarm robotics aims to use a large group of relatively simple robots to solve tasks that can hardly be achieved by a single robot in the group. Compared to single robot systems with increased capability, a swarm robotic system may have advantages in robustness, flexibility and scalability. However, designing cooperative behaviors for a swarm robotic system is a challenging problem, especially when the robots may not have communication capabilities and thus only know local information. For a swarm of miniature mobile robots that cannot communicate explicitly, this thesis studies fully decentralized solutions of two problems. For the problem of cooperative transport, the thesis presents a strategy to push an object that is large enough to occlude the robots' perception of the goal of the transportation. For the problem of pattern formation, the thesis investigates algorithms based on the Brazil nut effect that can organize the swarm of robots into an annular formation. These problems are studied using physics-based computer simulations as well as experimental implementations based on the e-puck robotic platform. The simplicity of the solutions make them suitable for applications that require the individual robots to be as simple as possible. Example application scenarios could be micro robot swarms working in the human body

Scalable Control Strategies and a Customizable Swarm Robotic Platform for Boundary Coverage and Collective Transport Tasks

abstract: Swarms of low-cost, autonomous robots can potentially be used to collectively perform tasks over large domains and long time scales. The design of decentralized, scalable swarm control strategies will enable the development of robotic systems that can execute such tasks with a high degree of parallelism and redundancy, enabling effective operation even in the presence of unknown environmental factors and individual robot failures. Social insect colonies provide a rich source of inspiration for these types of control approaches, since they can perform complex collective tasks under a range of conditions. To validate swarm robotic control strategies, experimental testbeds with large numbers of robots are required; however, existing low-cost robots are specialized and can lack the necessary sensing, navigation, control, and manipulation capabilities. To address these challenges, this thesis presents a formal approach to designing biologically-inspired swarm control strategies for spatially-confined coverage and payload transport tasks, as well as a novel low-cost, customizable robotic platform for testing swarm control approaches. Stochastic control strategies are developed that provably allocate a swarm of robots around the boundaries of multiple regions of interest or payloads to be transported. These strategies account for spatially-dependent effects on the robots' physical distribution and are largely robust to environmental variations. In addition, a control approach based on reinforcement learning is presented for collective payload towing that accommodates robots with heterogeneous maximum speeds. For both types of collective transport tasks, rigorous approaches are developed to identify and translate observed group retrieval behaviors in Novomessor cockerelli ants to swarm robotic control strategies. These strategies can replicate features of ant transport and inherit its properties of robustness to different environments and to varying team compositions. The approaches incorporate dynamical models of the swarm that are amenable to analysis and control techniques, and therefore provide theoretical guarantees on the system's performance. Implementation of these strategies on robotic swarms offers a way for biologists to test hypotheses about the individual-level mechanisms that drive collective behaviors. Finally, this thesis describes Pheeno, a new swarm robotic platform with a three degree-of-freedom manipulator arm, and describes its use in validating a variety of swarm control strategies.Dissertation/ThesisDoctoral Dissertation Mechanical Engineering 201

Light modulation of electric field driven semiconductor micromotors

The future micro/nanorobots require high degrees of freedom in motion control to perform complex tasks by individuals or by a swarm. It remains a great challenge to control the motions of an individual nanomachine amidst many, to switch the operation modes facilely, and it is even more difficult to actuate several components of a nanomachine coordinately for purposed actions. This high degree of versatility is essential for the future micro/nanorobots and requires investigation of innovative actuation mechanisms. In this dissertation, we report our recent finding about a new approach combining two types of stimulation to achieve such goal. The micromotors being studied are made of semiconductor silicon nanowires. Mechanical motion of the motors is driven by several types of AC electric field. Meanwhile, the electrical property of the nanowires can be locally and instantaneously modulated by visible light illumination in a reversible manner. We demonstrate that visible light is able to change the electric polarization of semiconductor nanowires under AC electric field, and reflected by the dramatic change of mechanical motions with very rich configurations. Under a rotating electric field, the rotation speed of semiconductor Si nanowires in electric fields can instantly increase, decrease, and even reverse the orientation by light illumination in the visible to infrared regime at various AC E-field frequencies. Under a linear AC electric field, instantaneous change of alignment direction and speed of semiconductor nanowires is observed under visible-light exposure. With theoretical analysis and simulation, the working principle can be attributed to the optically tuned imaginary-part (out-phase) and real-part (in-phase) electrical polarization of a semiconductor nanowire in aqueous suspension. Based on the understanding of this system, we further propose a new approach to control the semiconductor micromotor via light tunable dielectrophoresis. Localized control of collective behavior in a highly density silicon nanowire suspension is also investigated. Finally, we demonstrated how to utilize the mechanical motion at microscale for practical application of biosensing.Materials Science and Engineerin

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Active Materials

What is an active material? This book aims to redefine perceptions of the materials that respond to their environment. Through the theory of the structure and functionality of materials found in nature a scientific approach to active materials is first identified. Further interviews with experts from the natural sciences and humanities then seeks to question and redefine this view of materials to create a new definition of active materials

Active Materials

What is an active material? This book aims to redefine perceptions of the materials that respond to their environment. Through the theory of the structure and functionality of materials found in nature a scientific approach to active materials is first identified. Further interviews with experts from the natural sciences and humanities then seeks to question and redefine this view of materials to create a new definition of active materials

L’auto-exploration des espaces sensorimoteurs chez les robots

Developmental robotics has begun in the last fifteen years to study robots that havea childhood—crawling before trying to run, playing before being useful—and that are basing their decisions upon a lifelong and embodied experience of the real-world. In this context, this thesis studies sensorimotor exploration—the discovery of a robot’s own body and proximal environment—during the early developmental stages, when no prior experience of the world is available. Specifically, we investigate how to generate a diversity of effects in an unknown environment. This approach distinguishes itself by its lack of user-defined reward or fitness function, making it especially suited for integration in self-sufficient platforms. In a first part, we motivate our approach, formalize the exploration problem, define quantitative measures to assess performance, and propose an architectural framework to devise algorithms. through the extensive examination of a multi-joint arm example, we explore some of the fundamental challenges that sensorimotor exploration faces, such as high-dimensionality and sensorimotor redundancy, in particular through a comparison between motor and goal babbling exploration strategies. We propose several algorithms and empirically study their behaviour, investigating the interactions with developmental constraints, external demonstrations and biologicallyinspired motor synergies. Furthermore, because even efficient algorithms can provide disastrous performance when their learning abilities do not align with the environment’s characteristics, we propose an architecture that can dynamically discriminate among a set of exploration strategies. Even with good algorithms, sensorimotor exploration is still an expensive proposition— a problem since robots inherently face constraints on the amount of data they are able to gather; each observation takes a non-negligible time to collect. [...] Throughout this thesis, our core contributions are algorithms description and empirical results. In order to allow unrestricted examination and reproduction of all our results, the entire code is made available. Sensorimotor exploration is a fundamental developmental mechanism of biological systems. By decoupling it from learning and studying it in its own right in this thesis, we engage in an approach that casts light on important problems facing robots developing on their own.La robotique développementale a entrepris, au courant des quinze dernières années,d’étudier les processus développementaux, similaires à ceux des systèmes biologiques,chez les robots. Le but est de créer des robots qui ont une enfance—qui rampent avant d’essayer de courir, qui jouent avant de travailler—et qui basent leurs décisions sur l’expérience de toute une vie, incarnés dans le monde réel.Dans ce contexte, cette thèse étudie l’exploration sensorimotrice—la découverte pour un robot de son propre corps et de son environnement proche—pendant les premiers stage du développement, lorsque qu’aucune expérience préalable du monde n’est disponible. Plus spécifiquement, cette thèse se penche sur comment générer une diversité d’effets dans un environnement inconnu. Cette approche se distingue par son absence de fonction de récompense ou de fitness définie par un expert, la rendant particulièrement apte à être intégrée sur des robots auto-suffisants.Dans une première partie, l’approche est motivée et le problème de l’exploration est formalisé, avec la définition de mesures quantitatives pour évaluer le comportement des algorithmes et d’un cadre architectural pour la création de ces derniers. Via l’examen détaillé de l’exemple d’un bras robot à multiple degrés de liberté, la thèse explore quelques unes des problématiques fondamentales que l’exploration sensorimotrice pose, comme la haute dimensionnalité et la redondance sensorimotrice. Cela est fait en particulier via la comparaison entre deux stratégies d’exploration: le babillage moteur et le babillage dirigé par les objectifs. Plusieurs algorithmes sont proposés tour à tour et leur comportement est évalué empiriquement, étudiant les interactions qui naissent avec les contraintes développementales, les démonstrations externes et les synergies motrices. De plus, parce que même des algorithmes efficaces peuvent se révéler terriblement inefficaces lorsque leurs capacités d’apprentissage ne sont pas adaptés aux caractéristiques de leur environnement, une architecture est proposée qui peut dynamiquement choisir la stratégie d’exploration la plus adaptée parmi un ensemble de stratégies. Mais même avec de bons algorithmes, l’exploration sensorimotrice reste une entreprise coûteuse—un problème important, étant donné que les robots font face à des contraintes fortes sur la quantité de données qu’ils peuvent extraire de leur environnement;chaque observation prenant un temps non-négligeable à récupérer. [...] À travers cette thèse, les contributions les plus importantes sont les descriptions algorithmiques et les résultats expérimentaux. De manière à permettre la reproduction et la réexamination sans contrainte de tous les résultats, l’ensemble du code est mis à disposition. L’exploration sensorimotrice est un mécanisme fondamental du développement des systèmes biologiques. La séparer délibérément des mécanismes d’apprentissage et l’étudier pour elle-même dans cette thèse permet d’éclairer des problèmes importants que les robots se développant seuls seront amenés à affronter

Cyber-Human Systems, Space Technologies, and Threats

CYBER-HUMAN SYSTEMS, SPACE TECHNOLOGIES, AND THREATS is our eighth textbook in a series covering the world of UASs / CUAS/ UUVs / SPACE. Other textbooks in our series are Space Systems Emerging Technologies and Operations; Drone Delivery of CBNRECy – DEW Weapons: Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD); Disruptive Technologies with applications in Airline, Marine, Defense Industries; Unmanned Vehicle Systems & Operations On Air, Sea, Land; Counter Unmanned Aircraft Systems Technologies and Operations; Unmanned Aircraft Systems in the Cyber Domain: Protecting USA’s Advanced Air Assets, 2nd edition; and Unmanned Aircraft Systems (UAS) in the Cyber Domain Protecting USA’s Advanced Air Assets, 1st edition. Our previous seven titles have received considerable global recognition in the field. (Nichols & Carter, 2022) (Nichols, et al., 2021) (Nichols R. K., et al., 2020) (Nichols R. , et al., 2020) (Nichols R. , et al., 2019) (Nichols R. K., 2018) (Nichols R. K., et al., 2022)https://newprairiepress.org/ebooks/1052/thumbnail.jp