Interactive Robotic Manipulation of Elastic Objects

Duenser, Simon; Bern, James M.; Poranne, Roi; Coros, Stelian

doi:10.1109/iros.2018.8594291

Cited by 40 publications

(14 citation statements)

References 14 publications

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“…El sistema telerobótico YuMi de ABB combina diferentes capacidades para trabajar en entornos peligrosos, así como la atención al paciente [14]. compuesto por dos subsistemas, un sistema teleoperado formado por un YuMi, IRB14000 [7], doble brazo que incluye manos flexibles, sistemas de alimentación de piezas, localización de piezas mediante cámaras y control robótico deúltima generación, a este subsistema se les une un sistema de telepresencia, compuesto por una tablet, con un sistema de comunicación basado en WebRTC [12].…”

Section: Robot Colaborativo Teleoperado Con Doble Brazo Yumi (Abb Switzerland)unclassified

Estado del arte en robots de asistencia en hospitales, en entornos infecciosos (COVID-19)

Tirado-Bou¹,

Marín-Prades²,

Sanz³

et al. 2021

Xlii Jornadas De Automática : Libro De Actas

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En el presente artículo mostramos el estado del arte de los sistemas robóticos que están siendo desarrollados (algunos de los cuales ya en uso), para trabajar en entornos infecciosos, por ejemplo áreas de riesgo asociadas a COVID-19. Los sistemas permiten que el personal sanitario trabaje con mayor seguridad, e incrementan la seguridad también de los propios pacientes, permitiendo el seguimiento de los mismos, así como la desinfección de áreas expuestas al virus, entre otras potenciales aplicaciones. El trabajo futuro, mostrará el resultado de entrevistas con personal sanitario, los cuales han presentado requisitos para un potencial futuro sistema robótico asistencial en este ámbito.

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Section: Robot Colaborativo Teleoperado Con Doble Brazo Yumi (Abb Switzerland)unclassified

Estado del arte en robots de asistencia en hospitales, en entornos infecciosos (COVID-19)

Tirado-Bou¹,

Marín-Prades²,

Sanz³

et al. 2021

Xlii Jornadas De Automática : Libro De Actas

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“…The use of a model of a deformable object can allow precise and complete control of its shape. Finite-elementmethod models have been used for open-loop deformation control of elastic objects under dual-arm [23] and in-hand [24] manipulation. The work [25] studies shape servoing based on force feedback using a mass-springdamper model.…”

Section: Model-based Vs Model-free Deformable Manipulationmentioning

confidence: 99%

Monocular Visual Shape Tracking and Servoing for Isometrically Deforming Objects

Aranda

Ramón

Mezouar

et al. 2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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We address the monocular visual shape servoing problem. This pushes the challenging visual servoing problem one step further from rigid object manipulation towards deformable object manipulation. Explicitly, it implies deforming the object towards a desired shape in 3D space by robots using monocular 2D vision. We specifically concentrate on a scheme capable of controlling large isometric deformations. Two important open subproblems arise for implementing such a scheme. (P1) Since it is concerned with large deformations, perception requires tracking the deformable object's 3D shape from monocular 2D images which is a severely underconstrained problem. (P2) Since rigid robots have fewer degrees of freedom than a deformable object, the shape control becomes underactuated. We propose a template-based shape servoing scheme in which we solve these two problems. The template allows us to both infer the object's shape using an improved Shape-from-Template algorithm and steer the object's deformation by means of the robots' movements. We validate the scheme via simulations and real experiments.

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“…Various methods that explore analytical modeling approaches for non-rigid objects in robotic environments are inspired by physics-based models, extensively studied in computer graphics (Nealen et al, 2006 ). These include continuous mesh models such as Euler-Bernoulli (EB) (Fugl et al, 2012 ), linear Finite Element Method (FEM) (Lang et al, 2002 ; Frank et al, 2014 ; Jia et al, 2014 ; Petit et al, 2015 ; Duenser et al, 2018 ) and non-linear FEM (Leizea et al, 2017 ; Sengupta et al, 2020 ). Also, discrete mesh models such as linear Mass-Spring Systems (MSS) (Leizea et al, 2014 ) and non-linear MSS (Zaidi et al, 2017 ) are considered.…”

Section: Related Workmentioning

confidence: 99%

Combining Self-Organizing and Graph Neural Networks for Modeling Deformable Objects in Robotic Manipulation

Valencia

Payeur

2020

Front. Robot. AI

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Modeling deformable objects is an important preliminary step for performing robotic manipulation tasks with more autonomy and dexterity. Currently, generalization capabilities in unstructured environments using analytical approaches are limited, mainly due to the lack of adaptation to changes in the object shape and properties. Therefore, this paper proposes the design and implementation of a data-driven approach, which combines machine learning techniques on graphs to estimate and predict the state and transition dynamics of deformable objects with initially undefined shape and material characteristics. The learned object model is trained using RGB-D sensor data and evaluated in terms of its ability to estimate the current state of the object shape, in addition to predicting future states with the goal to plan and support the manipulation actions of a robotic hand.

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Interactive Robotic Manipulation of Elastic Objects

Cited by 40 publications

References 14 publications

Estado del arte en robots de asistencia en hospitales, en entornos infecciosos (COVID-19)

Estado del arte en robots de asistencia en hospitales, en entornos infecciosos (COVID-19)

Monocular Visual Shape Tracking and Servoing for Isometrically Deforming Objects

Combining Self-Organizing and Graph Neural Networks for Modeling Deformable Objects in Robotic Manipulation

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