13,341 research outputs found
Human-Machine Interface for Remote Training of Robot Tasks
Regardless of their industrial or research application, the streamlining of
robot operations is limited by the proximity of experienced users to the actual
hardware. Be it massive open online robotics courses, crowd-sourcing of robot
task training, or remote research on massive robot farms for machine learning,
the need to create an apt remote Human-Machine Interface is quite prevalent.
The paper at hand proposes a novel solution to the programming/training of
remote robots employing an intuitive and accurate user-interface which offers
all the benefits of working with real robots without imposing delays and
inefficiency. The system includes: a vision-based 3D hand detection and gesture
recognition subsystem, a simulated digital twin of a robot as visual feedback,
and the "remote" robot learning/executing trajectories using dynamic motion
primitives. Our results indicate that the system is a promising solution to the
problem of remote training of robot tasks.Comment: Accepted in IEEE International Conference on Imaging Systems and
Techniques - IST201
Development of an intelligent object for grasp and manipulation research
Kõiva R, Haschke R, Ritter H. Development of an intelligent object for grasp and manipulation research. Presented at the ICAR 2011, Tallinn, Estonia.In this paper we introduce a novel device, called iObject, which is equipped with tactile and motion tracking sensors that allow for the evaluation of human and robot grasping and manipulation actions. Contact location and contact force, object acceleration in space (6D) and orientation relative to the earth (3D magnetometer) are measured and transmitted wirelessly over a Bluetooth connection. By allowing human-human, human-robot and robot-robot comparisons to be made, iObject is a versatile tool for studying manual interaction.
To demonstrate the efficiency and flexibility of iObject for the study of bimanual interactions, we report on a physiological experiment and evaluate the main parameters of the considered dual-handed manipulation task
A short curriculum of the robotics and technology of computer lab
Our research Lab is directed by Prof. Anton Civit. It is an interdisciplinary group of 23
researchers that carry out their teaching and researching labor at the Escuela
Politécnica Superior (Higher Polytechnic School) and the Escuela de Ingeniería
Informática (Computer Engineering School). The main research fields are: a)
Industrial and mobile Robotics, b) Neuro-inspired processing using electronic spikes,
c) Embedded and real-time systems, d) Parallel and massive processing computer
architecture, d) Information Technologies for rehabilitation, handicapped and elder
people, e) Web accessibility and usability
In this paper, the Lab history is presented and its main publications and research
projects over the last few years are summarized.Nuestro grupo de investigación está liderado por el profesor Civit. Somos un grupo
multidisciplinar de 23 investigadores que realizan su labor docente e investigadora
en la Escuela Politécnica Superior y en Escuela de Ingeniería Informática. Las
principales líneas de investigaciones son: a) Robótica industrial y móvil. b)
Procesamiento neuro-inspirado basado en pulsos electrónicos. c) Sistemas
empotrados y de tiempo real. d) Arquitecturas paralelas y de procesamiento masivo.
e) Tecnología de la información aplicada a la discapacidad, rehabilitación y a las
personas mayores. f) Usabilidad y accesibilidad Web.
En este artículo se reseña la historia del grupo y se resumen las principales
publicaciones y proyectos que ha conseguido en los últimos años
AirCode: Unobtrusive Physical Tags for Digital Fabrication
We present AirCode, a technique that allows the user to tag physically
fabricated objects with given information. An AirCode tag consists of a group
of carefully designed air pockets placed beneath the object surface. These air
pockets are easily produced during the fabrication process of the object,
without any additional material or postprocessing. Meanwhile, the air pockets
affect only the scattering light transport under the surface, and thus are hard
to notice to our naked eyes. But, by using a computational imaging method, the
tags become detectable. We present a tool that automates the design of air
pockets for the user to encode information. AirCode system also allows the user
to retrieve the information from captured images via a robust decoding
algorithm. We demonstrate our tagging technique with applications for metadata
embedding, robotic grasping, as well as conveying object affordances.Comment: ACM UIST 2017 Technical Paper
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