909 resultados para Robot programming


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Nabigazioa robot mugikorretan eta pertsonen jarraipenerako sistema baten ebaluazioa

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Computer science and electrical engineering have been the great success story of the twentieth century. The neat modularity and mapping of a language onto circuits has led to robots on Mars, desktop computers and smartphones. But these devices are not yet able to do some of the things that life takes for granted: repair a scratch, reproduce, regenerate, or grow exponentially fast–all while remaining functional.

This thesis explores and develops algorithms, molecular implementations, and theoretical proofs in the context of “active self-assembly” of molecular systems. The long-term vision of active self-assembly is the theoretical and physical implementation of materials that are composed of reconfigurable units with the programmability and adaptability of biology’s numerous molecular machines. En route to this goal, we must first find a way to overcome the memory limitations of molecular systems, and to discover the limits of complexity that can be achieved with individual molecules.

One of the main thrusts in molecular programming is to use computer science as a tool for figuring out what can be achieved. While molecular systems that are Turing-complete have been demonstrated [Winfree, 1996], these systems still cannot achieve some of the feats biology has achieved.

One might think that because a system is Turing-complete, capable of computing “anything,” that it can do any arbitrary task. But while it can simulate any digital computational problem, there are many behaviors that are not “computations” in a classical sense, and cannot be directly implemented. Examples include exponential growth and molecular motion relative to a surface.

Passive self-assembly systems cannot implement these behaviors because (a) molecular motion relative to a surface requires a source of fuel that is external to the system, and (b) passive systems are too slow to assemble exponentially-fast-growing structures. We call these behaviors “energetically incomplete” programmable behaviors. This class of behaviors includes any behavior where a passive physical system simply does not have enough physical energy to perform the specified tasks in the requisite amount of time.

As we will demonstrate and prove, a sufficiently expressive implementation of an “active” molecular self-assembly approach can achieve these behaviors. Using an external source of fuel solves part of the the problem, so the system is not “energetically incomplete.” But the programmable system also needs to have sufficient expressive power to achieve the specified behaviors. Perhaps surprisingly, some of these systems do not even require Turing completeness to be sufficiently expressive.

Building on a large variety of work by other scientists in the fields of DNA nanotechnology, chemistry and reconfigurable robotics, this thesis introduces several research contributions in the context of active self-assembly.

We show that simple primitives such as insertion and deletion are able to generate complex and interesting results such as the growth of a linear polymer in logarithmic time and the ability of a linear polymer to treadmill. To this end we developed a formal model for active-self assembly that is directly implementable with DNA molecules. We show that this model is computationally equivalent to a machine capable of producing strings that are stronger than regular languages and, at most, as strong as context-free grammars. This is a great advance in the theory of active self- assembly as prior models were either entirely theoretical or only implementable in the context of macro-scale robotics.

We developed a chain reaction method for the autonomous exponential growth of a linear DNA polymer. Our method is based on the insertion of molecules into the assembly, which generates two new insertion sites for every initial one employed. The building of a line in logarithmic time is a first step toward building a shape in logarithmic time. We demonstrate the first construction of a synthetic linear polymer that grows exponentially fast via insertion. We show that monomer molecules are converted into the polymer in logarithmic time via spectrofluorimetry and gel electrophoresis experiments. We also demonstrate the division of these polymers via the addition of a single DNA complex that competes with the insertion mechanism. This shows the growth of a population of polymers in logarithmic time. We characterize the DNA insertion mechanism that we utilize in Chapter 4. We experimentally demonstrate that we can control the kinetics of this re- action over at least seven orders of magnitude, by programming the sequences of DNA that initiate the reaction.

In addition, we review co-authored work on programming molecular robots using prescriptive landscapes of DNA origami; this was the first microscopic demonstration of programming a molec- ular robot to walk on a 2-dimensional surface. We developed a snapshot method for imaging these random walking molecular robots and a CAPTCHA-like analysis method for difficult-to-interpret imaging data.

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This thesis explores the problem of mobile robot navigation in dense human crowds. We begin by considering a fundamental impediment to classical motion planning algorithms called the freezing robot problem: once the environment surpasses a certain level of complexity, the planner decides that all forward paths are unsafe, and the robot freezes in place (or performs unnecessary maneuvers) to avoid collisions. Since a feasible path typically exists, this behavior is suboptimal. Existing approaches have focused on reducing predictive uncertainty by employing higher fidelity individual dynamics models or heuristically limiting the individual predictive covariance to prevent overcautious navigation. We demonstrate that both the individual prediction and the individual predictive uncertainty have little to do with this undesirable navigation behavior. Additionally, we provide evidence that dynamic agents are able to navigate in dense crowds by engaging in joint collision avoidance, cooperatively making room to create feasible trajectories. We accordingly develop interacting Gaussian processes, a prediction density that captures cooperative collision avoidance, and a "multiple goal" extension that models the goal driven nature of human decision making. Navigation naturally emerges as a statistic of this distribution.

Most importantly, we empirically validate our models in the Chandler dining hall at Caltech during peak hours, and in the process, carry out the first extensive quantitative study of robot navigation in dense human crowds (collecting data on 488 runs). The multiple goal interacting Gaussian processes algorithm performs comparably with human teleoperators in crowd densities nearing 1 person/m2, while a state of the art noncooperative planner exhibits unsafe behavior more than 3 times as often as the multiple goal extension, and twice as often as the basic interacting Gaussian process approach. Furthermore, a reactive planner based on the widely used dynamic window approach proves insufficient for crowd densities above 0.55 people/m2. We also show that our noncooperative planner or our reactive planner capture the salient characteristics of nearly any dynamic navigation algorithm. For inclusive validation purposes, we show that either our non-interacting planner or our reactive planner captures the salient characteristics of nearly any existing dynamic navigation algorithm. Based on these experimental results and theoretical observations, we conclude that a cooperation model is critical for safe and efficient robot navigation in dense human crowds.

Finally, we produce a large database of ground truth pedestrian crowd data. We make this ground truth database publicly available for further scientific study of crowd prediction models, learning from demonstration algorithms, and human robot interaction models in general.

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Life is the result of the execution of molecular programs: like how an embryo is fated to become a human or a whale, or how a person’s appearance is inherited from their parents, many biological phenomena are governed by genetic programs written in DNA molecules. At the core of such programs is the highly reliable base pairing interaction between nucleic acids. DNA nanotechnology exploits the programming power of DNA to build artificial nanostructures, molecular computers, and nanomachines. In particular, DNA origami—which is a simple yet versatile technique that allows one to create various nanoscale shapes and patterns—is at the heart of the technology. In this thesis, I describe the development of programmable self-assembly and reconfiguration of DNA origami nanostructures based on a unique strategy: rather than relying on Watson-Crick base pairing, we developed programmable bonds via the geometric arrangement of stacking interactions, which we termed stacking bonds. We further demonstrated that such bonds can be dynamically reconfigurable.

The first part of this thesis describes the design and implementation of stacking bonds. Our work addresses the fundamental question of whether one can create diverse bond types out of a single kind of attractive interaction—a question first posed implicitly by Francis Crick while seeking a deeper understanding of the origin of life and primitive genetic code. For the creation of multiple specific bonds, we used two different approaches: binary coding and shape coding of geometric arrangement of stacking interaction units, which are called blunt ends. To construct a bond space for each approach, we performed a systematic search using a computer algorithm. We used orthogonal bonds to experimentally implement the connection of five distinct DNA origami nanostructures. We also programmed the bonds to control cis/trans configuration between asymmetric nanostructures.

The second part of this thesis describes the large-scale self-assembly of DNA origami into two-dimensional checkerboard-pattern crystals via surface diffusion. We developed a protocol where the diffusion of DNA origami occurs on a substrate and is dynamically controlled by changing the cationic condition of the system. We used stacking interactions to mediate connections between the origami, because of their potential for reconfiguring during the assembly process. Assembling DNA nanostructures directly on substrate surfaces can benefit nano/microfabrication processes by eliminating a pattern transfer step. At the same time, the use of DNA origami allows high complexity and unique addressability with six-nanometer resolution within each structural unit.

The third part of this thesis describes the use of stacking bonds as dynamically breakable bonds. To break the bonds, we used biological machinery called the ParMRC system extracted from bacteria. The system ensures that, when a cell divides, each daughter cell gets one copy of the cell’s DNA by actively pushing each copy to the opposite poles of the cell. We demonstrate dynamically expandable nanostructures, which makes stacking bonds a promising candidate for reconfigurable connectors for nanoscale machine parts.

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[ES]Este Trabajo consiste en diseñar un robot de cinemática paralela de dos grados de libertad partiendo de unos requisitos mínimos necesarios que habrán de verificarse. A continuación, se fabricará siguiendo dicho diseño para finalmente montarlo sobre unas guías lineales constituyendo así una máquina de cinemática paralela, objetivo final conjunto de este Trabajo añadido al mencionado control de las guías. Resulta de especial interés su particular arquitectura, aspecto clave cuando se pretende un sistema preciso y reducir las vibraciones.

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[ES]El presente Trabajo de Fin de Grado tiene como objetivo contribuir al desarrollo de un proyecto de investigación mediante la programación y control del movimiento de mecanismos de cinemática paralela para la realización de ensayos dinámicos. Dicho proyecto está enmarcado dentro de una línea de investigación del grupo de investigación CompMech de la UPV-­‐EHU que gira en torno al desarrollo y estudio de este tipo de mecanismos. Esto es; este trabajo, más allá de la utilidad que pudiera tener por sí mismo, está pensado para formar parte de un proyecto de mayor envergadura, para cuyo éxito será imprescindible la colaboración con otros investigadores y la integración de este trabajo con los realizados por ellos. Consiste en la creación de un software para el control y movimiento de mecanismos, generando vibraciones para la realización de ensayos dinámicos. Para ello, se programarán sobre la plataforma LabVIEW la interfaz de usuario y el motor de cálculo. Una vez se compruebe que el programa funciona correctamente, se integrará dentro de un programa principal, un control articular que será el encargado de comunicarse con la máquina. Posteriormente, se procederá a la realización de ensayos experimentales sobre los propios robots, en taller. Se tomarán medidas mediante acelerómetros y otros dispositivos, determinando las medidas más adecuadas para su correcta validación. Finalmente, se generalizará el trabajo realizado para posibilitar su empleo futuro en diferentes mecanismos

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[EU]Gradu amaierako lan honetan, Industria Ingenieritza graduan zehar emandako zenbait irakasgaietan landutako kontzeptuak oinarri bezala hartuta SCARA robot industrialaren analisia egin da. Lau askatasun gradu dituzten robot hauek oso erabiliak dira industrian beraien lan ziklo azkar, karga handiak jasateko kapazitate, errepikortasun eta aplikazio ugariengatik. Proiektua, bi zati nagusitan banandu da: SCARA motako robot baten analisi zinematikoa, robotaren irudikapena eta ibilbideen sorkuntza Matlab programa erabiliz. Adept Cobra e-Vario 600, SCARA motako prototipo errealarekin interakzioa. Proiektuan zehar garatuko diren edukien egitura ondorengoa izango da: Lehenik eta behin, proiektuko lehen atalean proiektua kokatuta dagoen testuinguruaren azalpena emango da, baita ere testuinguru horrek gaur egun, sail desberdinetan, duen garrantzia. Proiektuko bigarren atalean, lana egiterakoan proposatu diren helburuak eta proiektuak eskaintzen dituen onurak adieraziko dira. Bestetik, proiektuko hirugarren atalean, gaiaren egoeran, SCARA robotera heldu arte robotek historian zehar izan duten garapena eta hauen sailkapen desberdinak azalduko dira. Laugarren atalean, metodologian, proiektu honetan garatuko diren bi zati nagusien deskribapen zehatza emango da. Azkenik, proiektuko azken atalean, lana burutzeko bete behar izan diren ataza bakoitzaren deskribapena eta iraupena, aurrekontua, arriskuen analisia eta proiektu honetatik atera ditugun ondorioak ematen dira.

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Over the last century, the silicon revolution has enabled us to build faster, smaller and more sophisticated computers. Today, these computers control phones, cars, satellites, assembly lines, and other electromechanical devices. Just as electrical wiring controls electromechanical devices, living organisms employ "chemical wiring" to make decisions about their environment and control physical processes. Currently, the big difference between these two substrates is that while we have the abstractions, design principles, verification and fabrication techniques in place for programming with silicon, we have no comparable understanding or expertise for programming chemistry.

In this thesis we take a small step towards the goal of learning how to systematically engineer prescribed non-equilibrium dynamical behaviors in chemical systems. We use the formalism of chemical reaction networks (CRNs), combined with mass-action kinetics, as our programming language for specifying dynamical behaviors. Leveraging the tools of nucleic acid nanotechnology (introduced in Chapter 1), we employ synthetic DNA molecules as our molecular architecture and toehold-mediated DNA strand displacement as our reaction primitive.

Abstraction, modular design and systematic fabrication can work only with well-understood and quantitatively characterized tools. Therefore, we embark on a detailed study of the "device physics" of DNA strand displacement (Chapter 2). We present a unified view of strand displacement biophysics and kinetics by studying the process at multiple levels of detail, using an intuitive model of a random walk on a 1-dimensional energy landscape, a secondary structure kinetics model with single base-pair steps, and a coarse-grained molecular model that incorporates three-dimensional geometric and steric effects. Further, we experimentally investigate the thermodynamics of three-way branch migration. Our findings are consistent with previously measured or inferred rates for hybridization, fraying, and branch migration, and provide a biophysical explanation of strand displacement kinetics. Our work paves the way for accurate modeling of strand displacement cascades, which would facilitate the simulation and construction of more complex molecular systems.

In Chapters 3 and 4, we identify and overcome the crucial experimental challenges involved in using our general DNA-based technology for engineering dynamical behaviors in the test tube. In this process, we identify important design rules that inform our choice of molecular motifs and our algorithms for designing and verifying DNA sequences for our molecular implementation. We also develop flexible molecular strategies for "tuning" our reaction rates and stoichiometries in order to compensate for unavoidable non-idealities in the molecular implementation, such as imperfectly synthesized molecules and spurious "leak" pathways that compete with desired pathways.

We successfully implement three distinct autocatalytic reactions, which we then combine into a de novo chemical oscillator. Unlike biological networks, which use sophisticated evolved molecules (like proteins) to realize such behavior, our test tube realization is the first to demonstrate that Watson-Crick base pairing interactions alone suffice for oscillatory dynamics. Since our design pipeline is general and applicable to any CRN, our experimental demonstration of a de novo chemical oscillator could enable the systematic construction of CRNs with other dynamic behaviors.

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[ES]En el siguiente Trabajo Fin de Grado se va a exponer el análisis cinemático y desarrollo de un modelo virtual para la implementación de las ecuaciones cinemáticas del robot IRB120 de ABB llevados a cabo durante el curso 2013/2014. Comenzando por un estudio del Estado del Arte de la robótica industrial, se plantean seguidamente las ecuaciones de localización del robot en función de las variables de entrada mediante el método matricial. Estas ecuaciones son implementadas en un modelo de MatLab para usarlas en la resolución del problema de posición directo e inverso, y son también usadas en herramientas de creación de trayectorias. Además, sus derivadas se utilizan en el cálculo de velocidades del elemento terminal. Por último, se muestra la creación del prototipo 3D del robot, así como un interfaz gráfico de control del robot para el usuario, y los trabajos de validación llevados a cabo de los mencionados modelos virtuales sobre el robot real.

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[ES]El presente Trabajo Fin de Grado: SIMULACIÓN DEL ROBOT DELTA MEDIANTE MATLAB trata sobre el robot Delta. El objetivo principal del trabajo es servir de base para futuros proyectos. Incluye información sobre los robots Delta, así como de sus aplicaciones. Este tipo de robots tienen numerosas aplicaciones y beneficios gracias a las numerosas características favorables que se mencionan a lo largo del trabajo, como lo es por ejemplo la gran velocidad a la que se puede mover. En el trabajo se verán las resoluciones de los problemas cinemáticos: directo e inverso. Además, se podrán describir trayectorias tomando como base los anteriores problemas cinemáticos. Finalmente, es especialmente interesante la introducción de los interpoladores en la generación de trayectorias y los beneficios que ello trae consigo.