• DocumentCode
    3315505
  • Title

    Pre-slip detection based Tactile Sensing

  • Author

    Petchartee, Somrak ; Monkman, Gareth

  • Author_Institution
    Univ. der Bundeswehr, Neubiberg
  • fYear
    2007
  • fDate
    3-6 Dec. 2007
  • Firstpage
    233
  • Lastpage
    238
  • Abstract
    Numerous researchers have investigated robot gripper manipulation control. A method to detect and reduce the risk of slippage by controlling the normal force as measured by tactile sensor arrays has been developed. A predictive model has been proposed which uses a basic method adapted to real applications in grasp optimization. Prevention of premature release with minimum prehension force is addressed without the need to measure the coefficient of friction between an object and a robot gripper. Predictive models have been used to develop a set of rules which predict the pre-slip based on fluctuations in tactile signal data. The proposed tactile sensor will be applied in grasp experimentation by identifying the least force required for prehension - the method appropriately called pre-slip detections. The subjects used for the experiments consist of objects with different sizes and weights.
  • Keywords
    force control; grippers; manipulators; sensor arrays; tactile sensors; fluctuations; grasp optimization; least force identification; normal force control; pre-slip detection based; predictive models; robot gripper manipulation control; slippage risk reduction; tactile sensor arrays; Force control; Force measurement; Force sensors; Grippers; Optimization methods; Predictive models; Robot control; Robot sensing systems; Sensor arrays; Tactile sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Sensors, Sensor Networks and Information, 2007. ISSNIP 2007. 3rd International Conference on
  • Conference_Location
    Melbourne, Qld.
  • Print_ISBN
    978-1-4244-1501-4
  • Electronic_ISBN
    978-1-4244-1502-1
  • Type

    conf

  • DOI
    10.1109/ISSNIP.2007.4496849
  • Filename
    4496849