Transferring Object Grasping Knowledge and Skill Across Different Robotic Platforms

被引:0
|
作者
Paikan, Ali [1 ]
Schiebener, David [2 ]
Waechter, Mirko [2 ]
Asfour, Tamim [2 ]
Metta, Giorgio [1 ]
Natale, Lorenzo [1 ]
机构
[1] IIT, iCub Facil, Genoa, Italy
[2] KIT, Lab H2T, Karlsruhe, Germany
关键词
D O I
暂无
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
This study describes the transfer of object grasping skills between two different humanoid robots with different software frameworks. We realize such a knowledge and skill transfer between the humanoid robots iCub and ARMAR-III. These two robots have different kinematics and are programmed using different middlewares, YARP and ArmarX. We developed a bridge system to allow for the execution of grasping skills of ARMAR-III on iCub. As the embodiment differs, the known feasible grasps for the one robot are not always feasible for the other robot. We propose a reactive correction behavior to detect failure of a grasp during its execution, to correct it until it is successful, and thus adapt the known grasp definition to the new embodiment.
引用
收藏
页码:498 / 503
页数:6
相关论文
共 50 条
  • [41] The Effectiveness of Storytelling in Transferring Different Types of Knowledge
    Katuscakova, Marcela
    Katuscak, Martin
    PROCEEDINGS OF THE 14TH EUROPEAN CONFERENCE ON KNOWLEDGE MANAGEMENT (ECKM 2013), VOLS 1 AND 2, 2013, : 341 - 348
  • [42] Transferring Information Across Medical Images of Different Modalities
    Nalepa, Jakub
    Mokry, Piotr
    Szymanek, Janusz
    Hayball, Michael P.
    PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION APPLICATIONS AND METHODS (ICPRAM 2018), 2018, : 526 - 533
  • [43] Transferring structural knowledge across cognitive maps in humans and models
    Shirley Mark
    Rani Moran
    Thomas Parr
    Steve W. Kennerley
    Timothy E. J. Behrens
    Nature Communications, 11
  • [44] Transferring structural knowledge across cognitive maps in humans and models
    Mark, Shirley
    Moran, Rani
    Parr, Thomas
    Kennerley, Steve W.
    Behrens, Timothy E. J.
    NATURE COMMUNICATIONS, 2020, 11 (01)
  • [45] Human-Robot Interaction for Assisted Object Grasping by a Wearable Robotic Object Manipulation Aid for the Blind
    Jin, Lingqiu
    Zhang, He
    Shen, Yantao
    Ye, Cang
    PROCEEDINGS OF THE 2020 IEEE INTERNATIONAL CONFERENCE ON HUMAN-MACHINE SYSTEMS (ICHMS), 2020, : 548 - 553
  • [46] Observing a human or a robotic hand grasping an object: differential motor priming effects
    Castiello, U
    Lusher, D
    Mari, M
    Edwards, M
    Humphreys, GW
    COMMON MECHANISMS IN PERCEPTION AND ACTION, 2002, 19 : 315 - 333
  • [47] Optimisation of Grasping Object Based on Pressure Sensor Measurement for Robotic Hand Gripper
    ALmassri, Ahmed M.
    WanHasan, W. Z.
    Ahmad, S. A.
    Ishak, A. J.
    Wada, Chikamune
    2015 9TH INTERNATIONAL CONFERENCE ON SENSING TECHNOLOGY (ICST), 2015, : 795 - 798
  • [48] Refining object proposals using structured edge and superpixel contrast in robotic grasping
    Chen, Lu
    Huang, Panfeng
    Zhao, Zhou
    ROBOTICS AND AUTONOMOUS SYSTEMS, 2018, 100 : 194 - 205
  • [49] Tactile object recognition in early phases of grasping using underactuated robotic hands
    da Fonseca, Vinicius Prado
    Jiang, Xianta
    Petriu, Emil M.
    de Oliveira, Thiago Eustaquio Alves
    INTELLIGENT SERVICE ROBOTICS, 2022, 15 (04) : 513 - 525
  • [50] Semantic Grasping: Planning Robotic Grasps Functionally Suitable for An Object Manipulation Task
    Dang, Hao
    Allen, Peter K.
    2012 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2012, : 1311 - 1317