1,720,954 research outputs found
Tactile sensing-based algorithms for perception of unknown objects
No full textDeveloping robotic platforms capable of accurately, reliably, and safely manipulating objects
requires equipping robots with a deep understanding of object perception. Humans integrate
tactile feedback and vision to have a more comprehensive understanding of objects. However,
in some occasions they need to rely on touch solely. To achieve human-like perception and
manipulation, robots must also handle unknown objects and interpret both dynamic and static
characteristics. To simultaneously perceive the diverse properties of real-world objects, such
as shape, texture, real-time contact force, and 6D pose, robots require a level of sensory
integration that traditional approaches typically lack. This Thesis primarily focuses on tactile
sensing to enable robots to perceive and manipulate unknown objects in varied, real-world
environments, and it explores how to integrate other modalities like proprioception to further
enhance perception. While much research in this area addresses known or specific categories
of objects, this work generalizes tactile perception to unseen objects and across various plat-
forms, emphasizing object-agnostic characteristics. By using machine learning techniques,
deep neural networks, classical control theory, and optimization methods, this thesis develops
algorithms and methods to enhance robots’ object perception and manipulation capabilities.
The proposed approaches rely on vision-based tactile sensors, which use a camera to capture
elastomer deformations and produce RGB images. This characteristic enables the employ-
ment of advanced deep learning techniques originally developed for visual data. The findings
of this research allow robots to classify local surfaces, adapt tactile data from simulations to
real-world tasks without loss of performance, estimate 6D object poses, predict 3D contact
forces from tactile data, and perform fine-grained manipulation tasks such as key insertion,
all using the same sensor technology. These methods, tested across diverse sensors and
environments, empower robots to perceive object characteristics in real time and manipulate
them more effectively. The results reveal that tactile sensing can significantly enhance robots
perception and manipulation capabilities, enabling lightweight, fast methods suitable for
real-time use. The proposed multisensory integrations broaden the potential applications of
tactile-enabled robots in fields requiring robust touch-based perception, including automated
assembly, healthcare, and service robotics. By advancing tactile sensing generalization and
multimodality across diverse objects and environments, this research lays a foundation for
autonomous robotic systems with intuitive, resilient perception and manipulation capabilities
akin to those of humans. All findings and methods are open-source, with the goal of creating
a multi-sensory library readily accessible to the community, fostering future research and
collaboration
Localization and Grasping of Objects by a Robot Arm Covered with Sensitive Skin
Full text linkLokalizace a uchopování předmětů roboty obvykle závisí na užití obrazových čidel. Hmatová zpětná vazba (HZV) s prostředím se užívá druhotně, nebo se nepoužívá vůbec. V této práci je zkoumán krajní případ, kdy nejsou dostupná jakákoliv obrazová data. Jedním takovým případem je robot s elektronickou kůží po celém svém těle. Navrhl jsem soustavu pro lokalizaci a uchopení předmětů pro tohoto robota v prostředí, kde se nachází vícero cílových objektů. Testoval jsem tento systém v prostředí s několika ručně vyrobenými předměty na stole. Systém dosahoval úspěšnosti 81.67, přičemž doba úchytu činila průměrně 207 s. Dále byla otestována varianta systému, která nepoužívá HZV při samotném úchytu. Tato varianta dosahovala úspěšnosti 64.14 % se snížením doby úchytu o 6.5 % na 194 s. Platforma a návrh systému kladou omezení na druh předmětu a jejich umístění, která je robot schopen uchopit. Budoucí práce by se měla zaměřit na stavbu robustnějších modelů předmětů. Data z velkého množství kontaktů, z přesnějšího dotykového senzoru, nebo oboje mohou být užita k tomuto účelu.Localization and grasping of objects by robots is typically performed while relying on some form of visual sensors. Haptic feedback from contacts with the environment is only secondary if present at all. In this work, an extreme case of localization and grasping in complete absence of visual input is explored. One such case is a robot that relies on a whole-body electronic skin. I designed a system for localization and grasping of objects for this robot in an environment with many target objects. I evaluated this system using several handmade objects on a table. The system achieved a grasp success rate of 81.67 % and average execution time of 207 s per object. A variant that does not use haptic feedback during grasping has shown a success rate of 64.14 % while decreasing the execution time by 6.5 % to 194 s. The platform and system design places severe limitations on general application, both in object type and pose. Future work should focus on the design of systems that predict object model using more information. A large number of contacts per object, a more detailed tactile sensor or both could be used for this purpose
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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