Virtual Haptic System for Shape Recognition Based on Local Curvatures

Guillem Garrofé, Carlota Parés, Anna Gutiérrez, Conrado Ruiz, Gerard Serra, David Miralles

Producción científica: Capítulo del libroContribución a congreso/conferenciarevisión exhaustiva

2 Citas (Scopus)


Haptic object recognition is widely used in various robotic manipulation tasks. Using the shape features obtained at either a local or global scale, robotic systems can identify objects solely by touch. Most of the existing work on haptic systems either utilizes a robotic arm with end-effectors to identify the shape of an object based on contact points, or uses a surface capable of recording pressure patterns. In this work, we introduce a novel haptic capture system based on the local curvature of an object. We present a haptic sensor system comprising of three aligned and equally spaced fingers that move towards the surface of an object at the same speed. When an object is touched, our system records the relative times between each contact sensor. Simulating our approach in a virtual environment, we show that this new local and low-dimensional geometrical feature can be effectively used for shape recognition. Even with 10 samples, our system achieves an accuracy of over 90 % without using any sampling strategy or any associated spatial information.

Idioma originalInglés
Título de la publicación alojadaAdvances in Computer Graphics - 38th Computer Graphics International Conference, CGI 2021, Proceedings
EditoresNadia Magnenat-Thalmann, Nadia Magnenat-Thalmann, Victoria Interrante, Daniel Thalmann, George Papagiannakis, Bin Sheng, Jinman Kim, Marina Gavrilova
EditorialSpringer Science and Business Media Deutschland GmbH
Número de páginas13
ISBN (versión impresa)9783030890285
EstadoPublicada - 2021
Evento38th Computer Graphics International Conference, CGI 2021 - Virtual, Online
Duración: 6 sept 202110 sept 2021

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen13002 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349


Conferencia38th Computer Graphics International Conference, CGI 2021
CiudadVirtual, Online


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