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Adaptive stable grasping control strategy based on slippage detection

Adaptive stable grasping control strategy based on slippage detection The authors want to design an adaptive grasping control strategy without setting the expected contact force in advance to maintain grasping stable, so that the proposed control system can deal with unknown object grasping manipulation tasks.Design/methodology/approachThe adaptive grasping control strategy is proposed based on bang-bang-like control principle and slippage detection module. The bang-bang-like control method is designed to find and set the expected contact force for the whole control system, and the slippage detection function is achieved by dynamic time warping algorithm.FindingsThe expected contact force can adaptively adjust in grasping tasks to avoid bad effects on the control system by the differences of prior test results or designers. Slippage detection can be recognized in time with variation of expected contact force manipulation environment in the control system. Based on if the slippage caused by an unexpected disturbance happens, the control system can automatically adjust the expected contact force back to the level of the previous stable state after a given time, and has the ability to identify an unnecessary increasing in the expected contact force.Originality/valueOnly contact force is used as feedback variable in control system, and the proposed strategy can save hardware components and electronic circuit components for sensing, reducing the cost and design difficulty of conducting real control system and making it easy to realize in engineering application field. The expected contact force can adaptively adjust due to unknown disturbance and slippage for various grasping manipulation tasks. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Industrial Robot: The International Journal of Robotics Research and Application Emerald Publishing

Adaptive stable grasping control strategy based on slippage detection

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0143-991X
DOI
10.1108/ir-01-2021-0024
Publisher site
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Abstract

The authors want to design an adaptive grasping control strategy without setting the expected contact force in advance to maintain grasping stable, so that the proposed control system can deal with unknown object grasping manipulation tasks.Design/methodology/approachThe adaptive grasping control strategy is proposed based on bang-bang-like control principle and slippage detection module. The bang-bang-like control method is designed to find and set the expected contact force for the whole control system, and the slippage detection function is achieved by dynamic time warping algorithm.FindingsThe expected contact force can adaptively adjust in grasping tasks to avoid bad effects on the control system by the differences of prior test results or designers. Slippage detection can be recognized in time with variation of expected contact force manipulation environment in the control system. Based on if the slippage caused by an unexpected disturbance happens, the control system can automatically adjust the expected contact force back to the level of the previous stable state after a given time, and has the ability to identify an unnecessary increasing in the expected contact force.Originality/valueOnly contact force is used as feedback variable in control system, and the proposed strategy can save hardware components and electronic circuit components for sensing, reducing the cost and design difficulty of conducting real control system and making it easy to realize in engineering application field. The expected contact force can adaptively adjust due to unknown disturbance and slippage for various grasping manipulation tasks.

Journal

Industrial Robot: The International Journal of Robotics Research and Application – Emerald Publishing

Published: Aug 19, 2021

Keywords: Control; Grippers; Robotics; Grasping manipulation; Adaptive control strategy; Slippage detection; Parameters adaptive adjusting

References

  • Assessing grasp stability based on learning and haptic data
    Bekiroglu, Y.; Laaksonen, J.; Jørgensen, J.A.; Kyrki, V.; Kragic, D.
  • Using tactile data for real-time feedback
    Berger, A.D.; Khosla, P.K.
  • Self-supervised regrasping using spatio-temporal tactile features and reinforcement learning
    Chebotar, Y.; Hausman, K.; Su, Z.; Sukhatme, G.S.; Schaal, S.
  • Edge tracking using tactile servo
    Chen, N.; Zhang, H.; Rink, R.
  • Tactile control based on Gaussian images and its application in bi-manual manipulation of deformable objects
    Delgado, A.; Corrales, J.A.; Mezouar, Y.; Lequievre, L.; Jara, C.; Torres, F.
  • In-hand recognition and manipulation of elastic objects using a servo-tactile control strategy
    Delgado, A.; Jara, C.A.; Torres, F.
  • Adaptive tactile control for in-hand manipulation tasks of deformable objects
    Delgado, A.; Jara, C.A.; Torres, F.
  • Hierarchical fingertip space: a unified framework for grasp planning and in-hand grasp adaptation
    Hang, K.; Li, M.; Stork, J.A.; Bekiroglu, Y.; Pokorny, F.T.; Billard, A.; Kragic, D.
  • ZMP features for touch driven robot control via tactile servo
    Kappassov, Z.; Ramon, J.A.C.; Perdereau, V.
  • Learning of grasp adaptation through experience and tactile sensing
    Li, M.; Bekiroglu, Y.; Kragic, D.; Billard, A.
  • A visuo-tactile control framework for manipulation and exploration of unknown objects
    Li, Q.; Haschke, R.; Ritter, H.
  • St-hmp: unsupervised spatio-temporal feature learning for tactile data
    Madry, M.; Bo, L.; Kragic, D.; Fox, D.
  • Active contour following to explore object shape with robot touch
    Martinez-Hernandez, U.; Dodd, T.J.; Natale, L.; Metta, G.; Prescott, T.J.; Lepora, N.F.
  • Learning continuous grasp stability for a humanoid robot hand based on tactile sensing
    Schill, J.; Laaksonen, J.; Przybylski, M.; Kyrki, V.; Asfour, T.; Dillmann, R.
  • Force estimation and slip detection/classification for grip control using a biomimetic tactile sensor
    Su, Z.; Hausman, K.; Chebotar, Y.; Molchanov, A.; Loeb, G.E.; Sukhatme, G.S.; Schaal, S.
  • Can modular finger control for in-hand object stabilization be accomplished by independent tactile feedback control laws?
    Veiga, F.; Peters, J.
  • Time-delay control using a novel nonlinear adaptive law for accurate trajectory tracking of cable-driven robots
    Wang, Y.; Liu, L.; Wang, D.; Ju, F.; Chen, B.
  • Adaptive time-delay control for cable-driven manipulators with enhanced nonsingular fast terminal sliding mode
    Wang, Y.; Li, S.; Wang, D.; Ju, F.; Chen, B.; Wu, H.
  • Slip detection: analysis and calibration of univariate tactile signals
    Wyk, K.; Falco, J.
  • Learning Spatio temporal tactile features with a convLSTM for the direction of slip detection
    Zapata-Impata, B.; Gil, P.; Torres, F.