96 research outputs found

    Biologically Inspired Robots

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    Rapid Polymer Prototyping for Low Cost and Robust Microrobots

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    The Rapid Microrobot Prototyping (RaMP) Process uses Loctite(R) photo-patternable polymer products and photolithography to rapidly fabricate robust, inexpensive, and compliant robots. The process is developed and examined on two size scales. On the size scale of several centimeters, two functional robots and a small gripper have been designed and demonstrated with shape memory alloy (SMA) used for actuation. The gripper is 1.2g and costs 3.21whiletheinchwormrobotis7.4gandcosts3.21 while the inchworm robot is 7.4g and costs 7.76 in small numbers. The second robot costs $14.93 in small numbers. On the sub-centimeter scale, designs and considerations for a walking microrobot fabricated with the process and its control are fully described. The design and kinematics of a thermally actuated, one degree of freedom leg for the microrobot are developed and simulated. Several of these units could be combined to rapidly build a 30 mg functional and simple walking microrobot with the ability to lift several grams

    DESIGN AND CONSTRUCTION OF A TREE CLIMBING ROBOT

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    This Project is on the design, construction, and testing of a robot to climb trees and to detect Asian Longhorn Beetle infestation. The primary goal was to design and build a robot that could successfully climb a tree. After researching existing climbing robot designs, a robot prototype was built using concepts from the existing designs. The prototype was then tested to determine the effectiveness of the design. The prototype proved to be partially successful, being capable of gripping a tree and staying on, but could not move. Though not entirely successful, the project identified many important aspects in a tree climbing robot\u27s design

    New Approaches to Multi-functional Soft Materials

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    Soft robotics is a relatively new, but fast-developing field of science and technology that utilizes soft materials such as polymers in their body structure. Despite significant progress in soft robotic devices, robots that can sense their environments are still very rare. Although some soft robots have exhibited sensing capabilities, they still have not demonstrated synergistic coupling of sensing and actuation. From our perspective, this type of coupling may take us one step closer to fabricate soft robots with autonomous feedback dynamics. In this work, we present new approaches to soft robotic devices, which are fabricated from responsive soft materials and are able to exhibit synergistic coupling of structural color-based sensing and actuation in response to environmental stimuli. Cephalopods, such as cuttlefish, are excellent models of coupled sensing and actuation. They demonstrate remarkable adaptability to the coloration and texture of their surroundings by modulating their skin color and surface morphology simultaneously and reversibly, for adaptive camouflage and signal communication. Inspired by this unique feature of cuttlefish skins, we present a general approach to remote-controlled, smart films that undergo simultaneous changes of surface color and morphology upon infrared (IR) actuation. The smart film has a reconfigurable laminated structure that comprises an IR-responsive nanocomposite actuator layer and a mechanochromic elastomeric photonic crystal layer. Upon global or localized IR irradiation, the actuator layer exhibits fast, large, and reversible strain in the irradiated region, which causes a synergistically coupled change in the shape of the laminated film and color of the mechanochromic elastomeric photonic crystal layer in the same region. Complex 3D shapes, such as bending and twisting deformations, can be created under IR irradiation, by modulating the strain direction in the actuator layer of the laminated film. Finally, the laminated film has been used in a remote-controlled inchworm walker that can directly couple a color-changing skin with the robotic movements. Such IR-actuated, reconfigurable films could enable new functions in soft robots and wearable devices. A crucial aspect of soft robotics is the sensing capabilities of the robot. Colorimetric sensing based on structural colors, mostly photonic crystals, has been explored. A major challenge is overcoming the problems of limited scalability and time-consuming fabrication process, which affect the real-world applications of photonic crystals. Herein, we have developed a new scalable and affordable platform technology for fabrication of stimuli-responsive, interference colored films. Our system is composed of a thin film of a transparent polymer deposited on a metal-coated substrate. The facile fabrication process allows us to create full spectrum of interference colors on both rigid and soft substrates by simply adjusting the thickness of the polymer layer. Furthermore, our films have been used as colorimetric sensors which undergo fast and reversible change of surface color upon changes in environmental humidity. Such polymer-based, responsive interference coloration could empower colorimetric sensing of various environmental stimuli (e.g. humidity, chemicals, heat, and mechanical forces), which could enable a wide range of applications

    SMA-Based Muscle-Like Actuation in Biologically Inspired Robots: A State of the Art Review

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    New actuation technology in functional or "smart" materials has opened new horizons in robotics actuation systems. Materials such as piezo-electric fiber composites, electro-active polymers and shape memory alloys (SMA) are being investigated as promising alternatives to standard servomotor technology [52]. This paper focuses on the use of SMAs for building muscle-like actuators. SMAs are extremely cheap, easily available commercially and have the advantage of working at low voltages. The use of SMA provides a very interesting alternative to the mechanisms used by conventional actuators. SMAs allow to drastically reduce the size, weight and complexity of robotic systems. In fact, their large force-weight ratio, large life cycles, negligible volume, sensing capability and noise-free operation make possible the use of this technology for building a new class of actuation devices. Nonetheless, high power consumption and low bandwidth limit this technology for certain kind of applications. This presents a challenge that must be addressed from both materials and control perspectives in order to overcome these drawbacks. Here, the latter is tackled. It has been demonstrated that suitable control strategies and proper mechanical arrangements can dramatically improve on SMA performance, mostly in terms of actuation speed and limit cycles

    Locomotion through morphology, evolution and learning for legged and limbless robots

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    Mención Internacional en el título de doctorRobot locomotion is concerned with providing autonomous locomotion capabilities to mobile robots. Most current day robots feature some form of locomotion for navigating in their environment. Modalities of robot locomotion includes: (i) aerial locomotion, (ii) terrestrial locomotion, and (iii) aquatic locomotion (on or under water). Three main forms of terrestrial locomotion are, legged locomotion, limbless locomotion and wheel-based locomotion. A Modular Robot (MR), on the other hand, is a robotic system composed of several independent unit modules, where, each module is a robot by itself. The objective in this thesis is to develop legged locomotion in a humanoid robot, as well as, limbless locomotion in modular robotic configurations. Taking inspiration from biology, robot locomotion from the perspective of robot’s morphology, through evolution, and through learning are investigated in this thesis. Locomotion is one of the key distinguishing characteristics of a zoological organism. Almost all animal species, and even some plant species, produce some form of locomotion. In the past few years, robots have been “moving out” of the factory floor and research labs, and are becoming increasingly common in everyday life. So, providing stable and agile locomotion capabilities for robots to navigate a wide range of environments becomes pivotal. Developing locomotion in robots through biologically inspired methods, also facilitates furthering our understanding on how biological processes may function. Connected modules in a configuration, exert force on each other as a result of interaction between each other and their environment. This phenomenon is studied and quantified, and then used as implicit communication between robot modules for producing locomotion coordination in MRs. Through this, a strong link between robot morphology and the gait that emerge in it is established. A variety of locomotion controller, some periodic-function based and some morphology based, are developed for MR locomotion and bipedal gait generation. A hybrid Evolutionary Algorithm (EA) is implemented for evolving gaits, both in simulation as well as in the real-world on a physical modular robotic configuration. Limbless gaits in MRs are also learnt by learning optimal control policies, through Reinforcement Learning (RL).En robótica, la locomoción trata de proporcionar capacidades de locomoción autónoma a robots móviles. La mayoría de los robots actuales tiene alguna forma de locomoción para navegar en su entorno. Los modos de locomoción robótica se pueden repartir entre: (i) locomoción aérea, (ii) locomoción terrestre, y (iii) locomoción acuática (sobre o bajo el agua). Las tres formas básicas de locomoción terrestre son la locomoción mediante piernas, la locomoción sin miembros, y la locomoción basada en ruedas. Un Robot Modular, por otra parte, es un sistema robótico compuesto por varios módulos independientes, donde cada módulo es un robot en sí mismo. El objetivo de esta tesis es el desarrollo de la locomoción mediante piernas para un robot humanoide, así como el de la locomoción sin miembros para varias configuraciones de robots modulares. Inspirándose en la biología, también se investiga en esta tesis el desarrollo de la locomoción del robot según su morfología, gracias a técnicas de evolución y de aprendizaje. La locomoción es una de las características distintivas de un organismo zoológico. Casi todas las especies animales, e incluso algunas especies de plantas, poseen algún tipo de locomoción. En los últimos años, los robots han “migrado” desde las fábricas y los laboratorios de investigación, y se están integrando cada vez más en nuestra vida diaria. Por estas razones, es crucial proporcionar capacidades de locomoción estables y ágiles a los robots para que puedan navegar por todo tipo de entornos. El uso de métodos de inspiración biológica para alcanzar esta meta también nos ayuda a entender mejor cómo pueden funcionar los procesos biológicos equivalentes. En una configuración de módulos conectados, puesto que cada uno interacciona con su entorno, los módulos ejercen fuerza los unos sobre los otros. Este fenómeno se ha estudiado y cuantificado, y luego se ha usado como comunicación implícita entre los módulos para producir la coordinación en la locomoción de este robot. De esta manera, se establece un fuerte vínculo entre la morfología de un robot y el modo de andar que este desarrolla. Se han desarrollado varios controladores de locomoción para robots modulares y robots bípedos, algunos basados en funciones periódicas, otros en la morfología del robot. Un algoritmo evolutivo híbrido se ha implementado para la evolución de locomociones, tanto en simulación como en el mundo real en una configuración física de robot modular. También se pueden generar locomociones sin miembros para robots modulares, determinando las políticas de control óptimo gracias a técnicas de aprendizaje por refuerzo. Se presenta en primer lugar en esta tesis el estado del arte de la robótica modular, enfocándose en la locomoción de robots modulares, los controladores, la locomoción bípeda y la computación morfológica. A continuación se describen cinco configuraciones diferentes de robot modular que se utilizan en esta tesis, seguido de cuatro controladores de locomoción. Estos controladores son el controlador heterogéneo, el controlador basado en funciones periódicas, el controlador homogéneo y el controlador basado en la morfología del robot. Se desarrolla como parte de este trabajo un controlador de locomoción lineal, periódico, basado en features, para la locomoción bípeda de robots humanoides. Los parámetros de control se ajustan primero a mano para reproducir un modelo cart-table, y el controlador se evalúa en un robot humanoide simulado. A continuación, gracias a un algoritmo evolutivo, la optimización de los parámetros de control permite desarrollar una locomoción sin modelo predeterminado. Se desarrolla como parte de esta tesis un enfoque sobre algoritmos de Embodied Evolución, en otras palabras el uso de robots modulares físicos en la fase de evolución. La implementación material, la configuración experimental, y el Algoritmo Evolutivo implementado para Embodied Evolución, se explican detalladamente. El trabajo también incluye una visión general de las técnicas de aprendizaje por refuerzo y de los Procesos de Decisión de Markov. A continuación se presenta un algoritmo popular de aprendizaje por refuerzo, llamado Q-Learning, y su adaptación para aprender locomociones de robots modulares. Se proporcionan una implementación del algoritmo de aprendizaje y la evaluación experimental de la locomoción generada.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Antonio Barrientos Cruz.- Secretario: Luis Santiago Garrido Bullón.- Vocal: Giuseppe Carbon

    Design, fabrication and mechanical optimization of multi-scale anisotropic feet for terrestrial locomotion

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    Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 67-69).Multi-scale surface interaction methods have been studied to achieve optimal locomotion over surface features of differing length scales. It has been shown that anisotropy is a convenient way of transferring an undirected force to a preferred direction or movement. In this thesis, the fundamentals of friction were studied to achieve a better understanding of how to design multi-scaled robotic feet that use anisotropy for terrestrial locomotion. Static and kinetic friction coefficients were found for novel test geometries under varying load conditions. The test geometries were manufactured with materials of variable durometer and were tested using unconventional rheometry methodology. Test results were then compared to standard friction laws. As predicted, the effects of contact area were shown to have an effect on the friction forces experienced by the softer materials. The contact area effects were then modeled as Hertzian contacts for a given material. Verification of the area dependencies for the materials with adhesive effects was performed for the samples used in the friction tests. The samples were subjected to varying compressive force and images of the corresponding contact areas were obtained using an inverted microscope. The microscope images were then processed using MATLAB's image processing toolbox to find the actual contact area for the samples. The contact area results were shown to be in accordance with Herztian contact principles. The effects of varying surface roughness were also studied for a given anisotropic arrangement of bristles. The array of bristles was used to provide propulsion to a controllable robot called BristleBot. The untethered nature of the robot allowed for unhindered velocity and force measurements that were used to analyze the effects of surface roughness. The force input for the robot was provided by two vibration motors that created an excitation which was then translated to horizontal movement by the anisotropic formation of the bristles. It was found that the BristleBot was able to achieve optimal locomotion when roughness conditions were minimized. Results of the anisotropic friction and adhesion tests were used to improve footpad development for soft robotic platforms.by Jeffrey W. Morin.S.M

    Algorithms for Modular Self-reconfigurable Robots: Decision Making, Planning, and Learning

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    Modular self-reconfigurable robots (MSRs) are composed of multiple robotic modules which can change their connections with each other to take different shapes, commonly known as configurations. Forming different configurations helps the MSR to accomplish different types of tasks in different environments. In this dissertation, we study three different problems in MSRs: partitioning of modules, configuration formation planning and locomotion learning, and we propose algorithmic solutions to solve these problems. Partitioning of modules is a decision-making problem for MSRs where each module decides which partition or team of modules it should be in. To find the best set of partitions is a NP-complete problem. We propose game theory based both centralized and distributed solutions to solve this problem. Once the modules know which set of modules they should team-up with, they self-aggregate to form a specific shaped configuration, known as the configuration formation planning problem. Modules can be either singletons or connected in smaller configurations from which they need to form the target configuration. The configuration formation problem is difficult as multiple modules may select the same location in the target configuration to move to which might result in occlusion and consequently failure of the configuration formation process. On the other hand, if the modules are already in connected configurations in the beginning, then it would be beneficial to preserve those initial configurations for placing them into the target configuration as disconnections and re-connections are costly operations. We propose solutions based on an auction-like algorithm and (sub) graph-isomorphism technique to solve the configuration formation problem. Once the configuration is built, the MSR needs to move towards its goal location as a whole configuration for completing its task. If the configuration’s shape and size is not known a priori, then planning its locomotion is a difficult task as it needs to learn the locomotion pattern in dynamic time – the problem is known as adaptive locomotion learning. We have proposed reinforcement learning based fault-tolerant solutions for locomotion learning by MSRs

    Developing Biomimetic Design Principles for the Highly Optimized and Robust Design of Products and Their Components

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    Engineering design methods focus on developing products that are innovative, robust, and multi-functional. In this context, the term robust refers to a product's ability to accomplish successfully its predetermined functions. Owing to the abundance of optimized and robust biological systems, engineering designers are now looking to nature for inspiration. Researchers believe that biomimetic or bio-inspired engineering systems can leverage the principles, mechanisms, processes, strategies, and/or morphologies of nature's successful designs. Unfortunately, two important problems associated with biomimetic design are a designer's limited knowledge of biology and the difference in biological and engineering terminologies. This research developed a new design tool that addresses these problems and proposes to help engineering designers develop candidate bio-inspired products or solutions. A methodology that helps users infer or extract biomimetic design principles from a given natural system or biomimetic product pair is described in this thesis. The method incorporates and integrates five existing design tools and theories to comprehensively investigate a given natural system or biomimetic product. Subsequently, this method is used to extract biomimetic design principles from 23 biomimetic products and natural systems. It is proposed that these principles have the potential to inspire ideas for candidate biomimetic products that are novel, innovative, and robust. The principle extraction methodology and the identified principles are validated using two separate case studies and a detailed analysis using the validation square framework. In the first case study, two students and the author use the principle extraction methodology to extract characteristics from a natural system and a biomimetic product pair. Results from this case study showed that the methodology effectively and repeatedly identifies system characteristics that exemplify inherent biomimetic design principles. In the second case study, the developed biomimetic design principles are used to inspire a solution for an engineering design problem. The resulting solution and its evaluation show that the design's achieved usefulness is linked to applying the biomimetic design principles. Similar to the TRIZ principles, the biomimetic design principles can inspire ideas for solutions to a given problem. The key difference is that designers using TRIZ leverage the solution strategies of engineering patents, while designers using the biomimetic design principles leverage nature’s solution strategies. The biomimetic design principles are compared to TRIZ and the BioTRIZ matrix
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