Micro/nanoscale magnetic robots for biomedical applications

Magnetic small-scale robots are devices of great potential for the biomedical field because of the several benefits of this method of actuation. Recent work on the development of these devices has seen tremendous innovation and refinement toward ​improved performance for potential clinical applications. This review briefly details recent advancements in small-scale robots used for biomedical applications, covering their design, fabrication, applications, and demonstration of ability, and identifies the gap in studies and the difficulties that have persisted in the optimization of the use of these devices. In addition, alternative biomedical applications are also suggested for some of the technologies that show potential for other functions. This study concludes that although the field of small-scale robot research is highly innovative ​there is need for more concerted efforts to improve functionality and reliability of these devices particularly in clinical applications. Finally, further suggestions are made toward ​the achievement of commercialization for these devices

Space-Time Continuous Models of Swarm Robotic Systems: Supporting Global-to-Local Programming

A generic model in as far as possible mathematical closed-form was developed that predicts the behavior of large self-organizing robot groups (robot swarms) based on their control algorithm. In addition, an extensive subsumption of the relatively young and distinctive interdisciplinary research field of swarm robotics is emphasized. The connection to many related fields is highlighted and the concepts and methods borrowed from these fields are described shortly

Characterization and control of artificial magnetotactic tetrahymena pyriformis

Micro-scale robotic systems have drawn a great deal of interest from researchers for their potential applications. Emerging areas, such as micromanufacturing and biosensing, look to integrate micro-scale robotics with biofactory-on-a-chip systems to solve engineering problems. To accomplish this goal, robots must be developed to work in a variety of micro-scale environments. This has led to the creation of artificial and biological microrobots. Artificial microrobots are expensive and challenging to produce as well as power. Alternatively, biological microrobots employ microorganisms that are easily and inexpensively cultured. Microorganisms also draw chemical energy from their surround environment eliminating the need for a power source. This makes microorganisms, such as Tetrahymena pyriformis (T. pyriformis), an appealing choice to use as microrobots.In this thesis, the utilization of T. pyriformis as a microrobot or cellular robot is demonstrated. The technique for culturing and fabricating magnetotactic cells is described. The experimental setup allowing for observation and control of T. pyriformis using magnetotaxis is presented. T. pyriformis swimming parameters are then characterized and applied to control the cells for engineering tasks. This work shows that T. pyriformis is a great candidate to be used as a cellular robot.M.S., Mechanical Engineering -- Drexel University, 201

Classification and Management of Computational Resources of Robotic Swarms and the Overcoming of their Constraints

Swarm robotics is a relatively new and multidisciplinary research field with many potential applications (e.g., collective exploration or precision agriculture). Nevertheless, it has not been able to transition from the academic environment to the real world. While there are many potential reasons, one reason is that many robots are designed to be relatively simple, which often results in reduced communication and computation capabilities. However, the investigation of such limitations has largely been overlooked. This thesis looks into one such constraint, the computational constraint of swarm robots (i.e., swarm robotics platform). To achieve this, this work first proposes a computational index that quantifies computational resources. Based on the computational index, a quantitative study of 5273 devices shows that swarm robots provide fewer resources than many other robots or devices. In the next step, an operating system with a novel dual-execution model is proposed, and it has been shown that it outperforms the two other robotic system software. Moreover, results show that the choice of system software determines the computational overhead and, therefore, how many resources are available to robotic software. As communication can be a key aspect of a robot's behaviour, this work demonstrates the modelling, implementing, and studying of an optical communication system with a novel dynamic detector. Its detector improves the quality of service by orders of magnitude (i.e., makes the communication more reliable). In addition, this work investigates general communication properties, such as scalability or the effects of mobility, and provides recommendations for the use of such optical communication systems for swarm robotics. Finally, an approach is shown by which computational constraints of individual robots can be overcome by distributing data and processing across multiple robots

Climbing and Walking Robots

Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study

Swarm robotic systems: ypod formation with analysis on scalability and stability

Aquesta tesi se central en la formació d’eixams, on s’estudia el comportament coordinat d’un grup de robots per formar un patró quan s’observa a nivell global. En aquest sentit, la formació de la forma general és un dels problemes actuals en d’intel·ligència d’eixams artificials. En aquesta tesi s’introdueix una nova formació en forma de Y, la qual presenta una gran quantitat d’aplicacions en comparació amb altres tècniques de formació. Per exemple, la formació en Y es pot aplicar com a formació estratègica per totes les escales, presenta facilitat per canviar de forma i grandària a més de resoldre els problemes de redundància, d’autoorganització i autoreparació. L’objectiu principal d’aquesta tesi és aconseguir la formació en Y d’un eixam de robots. La implementació de dita formació únicament s’ha dut a terme mitjançant un entorn de simulació tot i que se han tingut en compte diferents aspectes que es podrien donar en una implementació real. El disseny del control de l’eixam per a diferents eixos s’ha realitzat a partir d’un model capaç de predir el comportament global de l’eixam, de la definició del temps d’establiment i l’aplicació de tècniques de localització de pols. Per controlar l’eixam en forma Y en termes d’orientació i el seu moviment com un bloc, s’han combinat el controlador lineal proposat, amb funcions límit i l’ajust d’alguns paràmetres per simulació. Els paràmetres s’han escollit per la formació desitjada i segons les constants definides per l’usuari. En comparació amb altres treballs, la solució proposta és simple, computacionalment eficient i tant per models d’eixams centralitzats com descentralitzats.Esta tesis se centra en la formación de enjambres, donde se estudia el comportamiento coordinado de un grupo de robots para formar un patrón cuando se observa a nivel global. En este sentido, la formación de la forma general es uno de los problemas actuales en la inteligencia de enjambres artificiales. En esta tesis se introduce una nueva formación en forma de Y, la cual presenta una gran cantidad de aplicaciones en comparación con otras técnicas de formación. Por ejemplo, la formación en Y se puede aplicar como formación estratégica para todas las escalas, presenta facilidad para cambiar de forma y tamaño además de resolver los problemas de redundancia, de auto-organización y auto-reparación. El objetivo principal de esta tesis es conseguir la formación en Y de un enjambre de robots. La implementación de dicha formación se ha llevado a cabo únicamente mediante un entorno de simulación aunque se han tenido en cuenta diferentes aspectos que se podrían dar en una implementación real. El diseño del control del enjambre para diferentes ejes se ha realizado a partir de un modelo capaz de predecir el comportamiento global del enjambre, de la definición del tiempo de establecimiento y la aplicación de técnicas de localización de polos. Para controlar el enjambre en forma de Y en términos de orientación y movimientos del enjambre como un bloque, se han combinado el controlador lineal propuesto, funciones límite y el ajuste de algunos parámetros por simulación. Los parámetros se han escogido para la formación deseada y según las constantes definidas por el usuario. En comparación con otros trabajos, la solución propuesta es simple, computacionalmente eficiente, y tanto para modelos de enjambres centralizados como descentralizados.The context of this work is the innovative young filed of swarm robotics. Particularly, in this thesis focused on swarm formation, which is important in swarm robotics too since coordinated behaviour of a group of robots to form a pattern when viewed globally. In this regard, global shape formation is one of the ongoing problems in artificial swarm intelligence. In nature, it is performed for various purposes, and search and rescue swarms could be used in disaster areas .In robotics phenomena, there exist various shape formations in the literature, but in this thesis, introduced new shape formation Y-Pod, which has vast applications compare to other formation techniques. In the discussion of our research journey, me and my supervisor discussed about various shape formations but finally exploit new shape formation Y-Pod and when we think about it, arise some questions ,why Y-Pod swarm formation and what it will serve, so in our casual discussion some important advantages are identified, those are : The Y-Pod can be utilized for formation strategy on all scales, Global shape formation, when viewed globally, Changes shapes, Easy to expand, overcome the redundancy problems and Self-organized and self-repair problems. The main objective of the proposed approach is to form a Y-pod formation of swarm robots. As well as we keep in our mind for real robot performance task, but the original work is delivered in simulation based environment only. Several parameters that significantly define the resulting behavior. We have proposed system equilibrium parameters with settling time and pole based problems, to control the swarm system in various axis an accurate model will predict the global behavior of the Y-Pod swarm formation based on the mathematical identified parameters. The proposed linear controller, limiting functions and simulation tuned parameters are combined to control Y-Pod swarm formation in terms of orientation, and swarm movement as a whole. Parameters are chosen based on desired formation as well as user defined constraints. This approach compared to others, is simple, computationally efficient, scales well to different swarm sizes, to heterogeneous systems, and to both centralized and decentralized swarm models

Ergodic Flocking of Swarm Robots

The design of efficient control strategies is a well studied problem. Due to recent technological advancements and applications in the field of robotics, exploring novel ways to design optimal control for multi-robot systems has gained interest. In this respect, the concept of ergodicity has successfully been applied as an effective control technique for tracking and area coverage. The generation of flocking behaviour is a problem that involves both tracking and coverage, and as such is also suited for the use of ergodicity. The main contribution of this thesis is the application of ergodicity to emulate flocking behaviour. This approach is appealing because control and communication is assumed to be local, self-organized, and does not require separate algorithms in order to generate different behaviour. Simulation results show that the proposed approach is effective and a prototype provides evidence that flocking behaviour is possible using ergodicity in a real-life setting.roboticsflocking behaviourergodicityalgorithmssimulatio

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