Visual grasp point localization, classification and state recognition in robotic manipulation of cloth: an overview

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Cloth manipulation by robots is gaining popularity among researchers because of its relevance, mainly (but not only) in domestic and assistive robotics. The required science and technologies begin to be ripe for the challenges posed by the manipulation of soft materials, and many contributions have appeared in the last years. This survey provides a systematic review of existing techniques for the basic perceptual tasks of grasp point localization, state estimation and classification of cloth items, from the perspective of their manipulation by robots. This choice is grounded on the fact that any manipulative action requires to instruct the robot where to grasp, and most garment handling activities depend on the correct recognition of the type to which the particular cloth item belongs and its state. The high inter- and intraclass variability of garments, the continuous nature of the possible deformations of cloth and the evident difficulties in predicting their localization and extension on the garment piece are challenges that have encouraged the researchers to provide a plethora of methods to confront such problems, with some promising results. The present review constitutes for the first time an effort in furnishing a structured framework of these works, with the aim of helping future contributors to gain both insight and perspective on the subjectPeer ReviewedPostprint (author's final draft

Implementação do algoritmo de Richardson-Lucy em arquiteturas reconfiguráveis aplicado ao problema de borramento de imagens

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Mecânica, 2015.Este trabalho apresenta a implementação em hardware de um algoritmo para a restauração para imagens que tenham sofrido degradação por movimento relativo entre a câmera e a cena (motion blur). O borramento da imagem é modelado matematicamente com o processo de convolução entre a função de degradação (Point Spread Function-PSF) e a imagem real, sendo a restauração da imagem real o processo inverso (deconvolução). O algoritmo de restauração implementado neste trabalho é conhecido como algoritmo de Richardson-Lucy (RLA). Neste caso, implementou-se o RLA em uma plataforma hardware FPGA (Field Programmable Gate Array) usando a linguagem de descrição de hardware VHDL (Very Hight Description Language), assumindo ausência de ruído aditivo no sistema de captura da imagem. A metodologia para avaliar a plataforma consistiu em simular a arquitetura projetada no ModelSim, fornecendo como dados de entradas as imagens degradadas. A degradação das imagens foi obtida usando a funções fspecial e imfilter do Matlab, as quais permitiram simular o borramento de imagens por movimentos da câmera (deslocamento e ângulo). Adicionalmente, a avaliação da qualidade das imagens coletadas foi realizada usando a métrica SR-SIM (Spectral Residual Based Similarity), assim como executando uma verificação visual das mesmas. O sistema implementado fornece um pixel processado por cada ciclo de relógio da FPGA, depois de um tempo de latência, sendo 12.425 vezes mais rápido que o mesmo algoritmo implementado no processador NIOS II. Adicionalmente foram feitas comparações rodando o algoritmo em um PC Intel Core-i3 a 3,2GHz. Neste caso, a implementação do algoritmo foi realizada usando a biblioteca OpenCV. Resultados de simulações e testes com imagens reais são apresentados para dar suporte à aplicabilidade em vídeo.This work presents the hardware implementation of an image restoration algorithm, in which the images are blurred by relative motion between camera and the scene. The blurred image process is mathematically modeled by a convolution process between the original image and the pointspread function (PSF) of the blurring system, being the image restoration the inverse process (a deconvolution process). The restoration algorithm that was implemented in this work is known as Richardson-Lucy (RLA) algorithm. In this case the RLA was implemented in an FPGA-based platform using the hardware description language VHDL (Very Hight Description Language), and assuming the absence of additive noise in the capturing image system. The methodology for evaluating the platform consists of simulating the designed architecture in the ModelSim platform, providing as data input the blurred images. The blurring process of the images was achieved by using the Matlab functions fspecial e imfilter, which allowed the simulation of blurred images by camera movements (displacement and angle). Additionally, the quality evaluation of the collected images was achieved using the SR-SIM (Spectral Residual Based Similarity) metric as well as by a visual verification of the images. The implemented system provides a processed pixel per clock cycle of the FPGA, after a latency time, being 12.425 times faster than the same algorithm implemented in software (running in the NIOS processor at 100 MHz). Additionally, comparisons have being done by running the same algorithm in a PC Intel Core-i3 with 3,2GHz. In this case, the algorithm implementation was developed using the OpenCV library. The results of simulations and respective testing with real images are also presented in order to give support to video applications