Model of tactile sensors using soft contacts and its application in robot grasping simulation

被引:15
|
作者
Moisio, Sami [1 ]
Leon, Beatriz [2 ]
Korkealaakso, Pasi [1 ]
Morales, Antonio [2 ]
机构
[1] Lappeenranta Univ Technol, Ctr Computat Engn & Integrated Design CEID, Lab Intelligent Machines, Lappeenranta 53851, Finland
[2] Univ Jaume 1, Dept Comp Sci & Engn, Robot Intelligence Lab, Castellon de La Plana 12006, Spain
关键词
Tactile sensing; Dynamic simulation; Robot Grasping; Soft contacts;
D O I
10.1016/j.robot.2012.10.008
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the context of robot grasping and manipulation, realistic dynamic simulation requires accurate modeling of contacts between bodies and, in a practical level, accurate simulation of touch sensors. This paper addresses the problem of creating a simulation of a tactile sensor as well as its implementation in a simulation environment. The simulated tactile sensor model utilizes collision detection and response methods using soft contacts as well as a full friction description. The tactile element is created based on a geometry enabling the creation of a variety of different shape tactile sensors. The tactile sensor element can be used to detect touch against triangularized geometries. This independence in shape enables the use of the sensor model for various applications, ranging from regular tactile sensors to more complex geometries as the human hand which makes it possible to explore human-like touch. The developed tactile sensor model is implemented within OpenGRASP and is available in the open-source plugin. The model has been validated through several experiments ranging from physical properties verification to testing on robot grasping applications. This simulated sensor can provide researchers with a valuable tool for robotic grasping research, especially in cases where the real sensors are not accurate enough yet. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 12
页数:12
相关论文
共 50 条
  • [31] Taxim: An Example-Based Simulation Model for GelSight Tactile Sensors
    Si, Zilin
    Yuan, Wenzhen
    [J]. IEEE ROBOTICS AND AUTOMATION LETTERS, 2022, 7 (02) : 2361 - 2368
  • [32] Using Tactile Sensors to Estimate Care Receiver Position on Dual Arms of Robot
    Mori, Yuki
    Ikeura, Ryoujun
    Ding, Ming
    [J]. 2013 IEEE SENSORS, 2013, : 1242 - 1245
  • [33] Estimation of lightweight object's mass by a humanoid robot during a precision grip with soft tactile sensors
    Silva, Andre
    Brites, Maria
    Paulino, Tiago
    Moreno, Plinio
    [J]. 2019 THIRD IEEE INTERNATIONAL CONFERENCE ON ROBOTIC COMPUTING (IRC 2019), 2019, : 344 - 348
  • [34] Contact Localization and Force Estimation of Soft Tactile Sensors using Artificial Intelligence
    Kim, DongWook
    Park, Yong-Lae
    [J]. 2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2018, : 7480 - 7485
  • [35] Soft Tactile Sensing for Object Classification and Fine Grasping Adjustment Using a Pneumatic Hand With an Inflatable Palm
    Su, Manjia
    Huang, Dongyu
    Guan, Yisheng
    Xiang, Chaoqun
    Zhu, Haifei
    Liu, Zhi
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2024, 71 (04) : 3873 - 3883
  • [36] ELECTRO-MECHANICAL MODEL AND ITS APPLICATION TO BIPED-ROBOT STABILITY WITH FORCE SENSORS
    Maiti, Tapas K.
    Dutta, Sunandan
    Ochi, Yoshihiro
    Miura-Mattausch, Mitiko
    Mattausch, Hans J.
    [J]. INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION, 2022, 37 (04): : 332 - 345
  • [37] Classification of Prism Object Shapes Utilizing Tactile Spatiotemporal Differential Information Obtained from Grasping by Single-Finger Robot Hand with Soft Tactile Sensor Array
    Watanabe, Kenshi
    Ohkubo, Kenichi
    Ichikawa, Sumiaki
    Hara, Fumio
    [J]. JOURNAL OF ROBOTICS AND MECHATRONICS, 2007, 19 (01) : 85 - 96
  • [38] Learning a Curvature Dynamic Model of an Octopus-inspired Soft Robot Arm Using Flexure Sensors
    Kuppuswamy, Naveen
    Carbajal, Juan-Pablo
    [J]. PROCEEDINGS OF THE 2ND EUROPEAN FUTURE TECHNOLOGIES CONFERENCE AND EXHIBITION 2011 (FET 11), 2011, 7 : 294 - 296
  • [39] Superficial pain model using ANNs and its application to robot control
    Matsunaga, N
    Kuroki, A
    Kawaji, S
    [J]. 2005 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS, VOLS 1 AND 2, 2005, : 664 - 669
  • [40] Methods for Safe Human-Robot-Interaction Using Capacitive Tactile Proximity Sensors
    Navarro, Stefan Escaida
    Marufo, Maximiliano
    Ding, Yitao
    Puls, Stephan
    Goeger, Dirk
    Hein, Bjoern
    Woern, Heinz
    [J]. 2013 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2013, : 1149 - 1154