Textile Taxonomy and Classification Using Pulling and Twisting

Identification of textile properties is an important milestone toward advanced robotic manipulation tasks that consider interaction with clothing items such as assisted dressing, laundry folding, automated sewing, textile recycling and reusing. Despite the abundance of work considering this class of deformable objects, many open problems remain. These relate to the choice and modelling of the sensory feedback as well as the control and planning of the interaction and manipulation strategies. Most importantly, there is no structured approach for studying and assessing different approaches that may bridge the gap between the robotics community and textile production industry. To this end, we outline a textile taxonomy considering fiber types and production methods, commonly used in textile industry. We devise datasets according to the taxonomy, and study how robotic actions, such as pulling and twisting of the textile samples, can be used for the classification. We also provide important insights from the perspective of visualization and interpretability of the gathered data

Contact Force and Scanning Velocity during Active Roughness Perception

Haptic perception is bidirectionally related to exploratory movements, which means that exploration influences perception, but perception also influences exploration. We can optimize or change exploratory movements according to the perception and/or the task, consciously or unconsciously. This paper presents a psychophysical experiment on active roughness perception to investigate movement changes as the haptic task changes. Exerted normal force and scanning velocity are measured in different perceptual tasks (discrimination or identification) using rough and smooth stimuli. The results show that humans use a greater variation in contact force for the smooth stimuli than for the rough stimuli. Moreover, they use higher scanning velocities and shorter break times between stimuli in the discrimination task than in the identification task. Thus, in roughness perception humans spontaneously use different strategies that seem effective for the perceptual task and the stimuli. A control task, in which the participants just explore the stimuli without any perceptual objective, shows that humans use a smaller contact force and a lower scanning velocity for the rough stimuli than for the smooth stimuli. Possibly, these strategies are related to aversiveness while exploring stimuli

Behavior-grounded multi-sensory object perception and exploration by a humanoid robot

Infants use exploratory behaviors to learn about the objects around them. Psychologists have theorized that behaviors such as touching, pressing, lifting, and dropping enable infants to form grounded object representations. For example, scratching an object can provide information about its roughness, while lifting it can provide information about its weight. In a sense, the exploratory behavior acts as a ``question\u27\u27 to the object, which is subsequently ``answered by the sensory stimuli produced during the execution of the behavior. In contrast, most object representations used by robots today rely solely on computer vision or laser scan data, gathered through passive observation. Such disembodied approaches to robotic perception may be useful for recognizing an object using a 3D model database, but nevertheless, will fail to infer object properties that cannot be detected using vision alone. To bridge this gap, this dissertation introduces a framework for object perception and exploration in which the robot\u27s representation of objects is grounded in its own sensorimotor experience with them. In this framework, an object is represented by sensorimotor contingencies that span a diverse set of exploratory behaviors and sensory modalities. The results from several large-scale experimental studies show that the behavior-grounded object representation enables a robot to solve a wide variety of tasks including recognition of objects based on the stimuli that they produce, object grouping and sorting, and learning category labels that describe objects and their properties

Inference Algorithms and Sensorimotor Representations in Brains and Machines

Animals function in a 3D world in which survival depends on robust, well-controlled actions. Historically, researchers in Artificial Intelligence (AI) and neuroscience have explored sensory and motor systems independently. There is a growing body of literature in AI and neuroscience to suggest that they actually work in tandem. While there has been a great deal of work on vision and audition as sensory modalities in these fields, one could argue that a more fundamental modality in biology is haptics, or the sense of touch. In this thesis, we will look at building computational models that integrate tactile sensing with other sensory modalities to perform manipulation-like tasks in robots and discrimination tasks in mice. We will also explore the problem of inference through the lens of Markov Chain Monte Carlo methods (MCMC). We elaborate on the ideas discussed in this thesis in the introduction presented in Chapter 1. A challenging problem one often faces when applying probabilistic mathematical models to the study of sensory-motor systems and other problems involving learning of inference is sampling. Hamiltonian Markov Chain Monte Carlo (HMC) algorithms can efficiently draw representative samples from complex probabilistic models. Most MCMC methods rely on detailed balance to ensure that we can sample from the correct distribution. This constraint can be relaxed in discrete state spaces such as those employed by HMC type methods. In Chapter 2, we study HMC methods without detailed balance to explore faster convergence. Markov jump processes are stochastic processes on discrete state space but continuous in time. In Chapter 3, we use Markov Jump Processes to simulate waiting times along with generalized detailed balance. This waiting time ,we show, helps generate samples faster. Most MCMC methods are plagued by slow simulation times on discrete computing systems. In Chapter 4, we explore HMC in analog circuits where the problem of generating samples from a distribution is mapped to the problem of sampling charge in a capacitor.The second half of this dissertation focuses on the role of haptics in perception and action. Manipulation is a fundamental problem for artificial and biological agents. High dimensional actuators (say, fingers, trunks,etc) are really hard to control. In Chapter 5, we present an approach to learn to actuate dexterous manipulators to grasp objects in simulation. Haptics as a sensory modality is critical to many manipulation tasks. Employing haptics in high dimensional dextrous actuators is challenging. In Chapter 6, we explore how intrinsic curiosity and haptics can be used to learn exploration strategies for discrimination of objects with dextrous hands. A key component to make tactile sensing a possibility is the availability of cheap, efficient, scalable hardware. Chapter 7 presents results for tactile servoing using a physical gelsight sensor. Traditional neuroscience texts delineate sensory and motor systems as two independent systems yet recent results suggest that this may not be entirely complete. That is, there is evidence to suggest that the representations in the cortex is more distributed than is accepted. Finally in Chapter 8, we explore building a computational model of spiking neural data collected from both the barrel and motor cortices during free and active whisking. These works help towards understanding sensorimotor representations in the context of haptics and high dimensional controls. We conclude with a discussion on future directions in Chapter 9

Garras con sensores táctiles intrínsecos para manipular alimentos con robots

[EN] The primary handling of food with robots calls for the development of new manipulation devices, especially when products are easily damaged and have a wide range of shapes and textures. These difficulties are even greater in the agricultural industry because the quality of the products is also checked during the manual handling process. This PhD dissertation provides solutions to these issues and helps to further introduce robotics into the handling of food. Several methods for handling food are included and analyzed, and specific solutions are proposed and then validated with prototypes. The research focuses on devices capable of adapting themselves to the shapes of the products without increasing the complexity of the mechanism. After analyzing several different solutions, the method chosen involves the use of under-actuated mechanisms, compliant mechanisms and fingers with pads filled with granular fluids. These fluids can behave as quasi-liquids or quasi-solids due to the jamming transition, which provides a soft initial grasp and can support high stresses during fast movements performed by the robot. The additive manufacturing process provides an opportunity to develop robot grippers that are lighter, simpler, more flexible and cheaper. By using this process elastic mechanisms are manufactured in a single part, which are equivalent to mechanisms with several rigid parts connected by joints. Laser sintering is employed to produce pneumatic actuators, with different types of motions, based on the elastic properties of the materials used in this manufacturing process. As a result, the systems can be simplified to achieve grippers, with several fingers, that are produced as a single part. In order to estimate the freshness and quality of agricultural products while they are being grasped, accelerometers are added to the fingers of several grippers. Accelerometers are economical and act as intrinsic tactile sensors. They can be easily embedded, thereby reducing the risk of getting damaged due to contact with the product, and allow each of the grasping phases to be identified. To achieve good performance of the accelerometers, a specific process is defined for the robot gripper, which touches the products a few times. In addition, several gripper prototypes are manufactured with diverse under-actuated mechanisms, jamming systems, and a new program that processes the signals from the accelerometers using different procedures in order to obtain parameters that can be used to estimate the quality of products. These parameters are correlated with data from destructive tests that are commonly used as a reference. The best performance of the accelerometers is achieved when the finger employs a granular fluid, a correlation coefficient of 0.937 being accomplished for the ripeness of mangoes and 0.872 for the firmness of eggplants.[ES] La manipulación primaria de alimentos con robots precisa del desarrollo de nuevos sistemas de manipulación especialmente cuando los productos son sensibles al daño y presentan una amplia variabilidad de formas y texturas. En el sector agroalimentario las dificultades son aún mayores ya que la manipulación manual sirve además para inspeccionar los productos durante el proceso. Está tesis aporta soluciones a estos problemas facilitando la incorporación de la robótica. En la tesis se recopilan y analizan diversas soluciones para poder manipular alimentos proponiendo soluciones concretas que luego son validadas con prototipos. La investigación se centra en aquellos sistemas que son capaces de auto adaptarse a las formas de los productos sin incrementar la complejidad del mecanismo. Tras analizar diversas técnicas se propone el uso de mecanismos infra-actuados, mecanismos flexibles y dedos con fluidos granulares que, al estar encerrados dentro de una membrana, se comportan como cuasi-líquidos o cuasi-sólidos gracias a la transición jamming, permitiendo un agarre inicial suave y la posibilidad de transmitir esfuerzos elevados durante los movimientos del robot. En la búsqueda de garras más ligeras, sencillas, flexibles y económicas se aprovecha la oportunidad que brinda la tecnología de fabricación aditiva de material. Gracias a este proceso se fabrican mecanismos flexibles realizados en una única pieza y que equivalen a mecanismos de garras realizados con varias piezas rígidas unidos por articulaciones. Mediante el sinterizado por láser, se fabrican actuadores neumáticos, con diversos tipos de movimiento, basados en la flexibilidad del material empleado en su fabricación. En conjunto se simplifican los sistemas llegando a realizar garras flexibles de varios dedos fabricadas en una única pieza. Para evaluar la calidad y frescura de los productos agroalimentarios durante el agarre se emplean acelerómetros localizados en los dedos de varias garras. Los acelerómetros son económicos y se comportan como sensores táctiles intrínsecos, están fuera del contacto directo con el producto evitando desgastes por contacto y permiten identificar las distintas fases de agarre. Para lograr esto se desarrolla un proceso específico del robot con la garra, que palpa varias veces el producto. Se fabrican diversos tipos de garra con distintas tecnologías de mecanismos infra-actuados y sistemas jamming y se programa un algoritmo original de procesado de señal que con diversas técnicas es capaz de extraer parámetros de los acelerómetros que sirven para evaluar la calidad de los productos. Estos parámetros son correlacionados con los datos de ensayos destructivos que son habitualmente empleados como referencia. Las mejores capacidades se consiguen empleando garras con jamming lográndose coeficientes de correlación de 0.937 en índices de madurez con mangos y 0.872 en firmeza de berenjenas.[CA] La manipulació primària d'aliments amb robots precisa del desenvolupament de nous sistemes de manipulació especialment quan els productes són sensibles al dany i presenten una àmplia variabilitat de formes i textures. En el sector agroalimentari les dificultats són encara més grans ja que la manipulació manual serveix a més per a inspeccionar els productes durant el procés. Aquesta tesi aporta solucions a aquests problemes facilitant la incorporació de la robòtica. En la tesi es recopilen i analitzen diverses solucions per a poder manipular aliments proposant solucions concretes que després són validades amb prototips. La investigació es centra en aquells sistemes que són capaços d'auto adaptar-se a la forma dels productes sense incrementar la complexitat del mecanisme. Després d'analitzar diverses tècniques es proposa l'ús de mecanismes infra-actuats, mecanismes flexibles i dits amb fluids granulars que, tancats dins d'una membrana, es comporten com quasi-líquids o quasi-sòlids gràcies a la transició jamming, permetent una prensió inicial suau i la possibilitat de transmetre esforços elevats durant els moviments del robot. En la recerca d'urpes més lleugeres, senzilles, flexibles i econòmiques s'aprofita l'oportunitat que brinda la tecnologia de fabricació additiva de material. Gràcies a aquest procés es fabriquen mecanismes flexibles realitzats en una única peça i que equivalen a mecanismes d'urpes realitzats amb diverses peces rígides unides per articulacions. Mitjançant el sinteritzat per làser, es fabriquen actuadors pneumàtics, amb diversos tipus de moviment, basats en la flexibilitat del material emprat en la seva fabricació. En conjunt es simplifiquen els sistemes arribant a realitzar urpes flexibles de diversos dits fabricades en una única peça. Per a avaluar la qualitat i frescor dels productes agroalimentaris durant la manipulació s'empren acceleròmetres localitzats en els dits de diverses urpes. Els acceleròmetres són econòmics i es comporten com a sensors tàctils intrínsecs, sense estar en contacte directe amb el producte evitant desgastos per aquest motiu, i permeten identificar les diferents fases d'prensió. Per aconseguir això es desenvolupa un procés específic del robot amb l'urpa, que palpa diverses vegades el producte. Es fabriquen diversos tipus d'urpa amb diferents tecnologies de mecanismes infra-actuats i sistemes jamming i es programa un algoritme original de processat de senyal que, amb diverses tècniques, és capaç d'extreure paràmetres dels acceleròmetres que serveixen per a avaluar la qualitat dels productes. Aquests paràmetres són correlacionats amb les dades d'assajos destructius que són habitualment emprats com a referència. Les millors capacitats s'aconsegueixen emprant urpes amb jamming assolint-se coeficients de correlació de 0,937 en índexs de maduresa amb mangos i 0,872 en fermesa d'albergínies.Blanes Campos, C. (2016). Garras con sensores táctiles intrínsecos para manipular alimentos con robots [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/68481TESI