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RoManSy 6 pp 283-295 | Cite as

Adaptative Force Control of Grippers Taking into Account the Dynamics of Objects

  • T. Fukuda
  • N. Kitamura
  • K. Tanie

Abstract

In this paper, a force control method for grippers is presented, dynamics of objects based on adaptive control, as demonstrated by experiments being also considered. Since present industrial robotic grippers commonly employ the input/output position control method and sometimes the force control method, it is of great interest to control both the force and position of the gripper against the object simultaneously, However, it is not easy to control the gripper without knowing the nature of the objects, because the dynamics of the object inevitably comes into the overall feedback control system.

Some of the research in this area has been carried out employing steady state position error and various force sensors. Force control is increasingly demanding more sophisticated control for robotic grippers, and this type of gripper requires much more flexible control, such as the handling of various objects adaptively with consideration both of position and force. The adaptive method applicable to say all types of gripper systems, as proposed here, advocates that it is possible to take into account the dynamics of objects by identifying the dynamics via the model reference adaptive system from the viewpoint of force and position control. The proposed method is applied to a gripper handling object. The gripper can hold various objects adaptively with smaller impact forces applied; hence it does not damage objects, unlike conventional grippers. Thus, the range of applicability of force control can be increased with 284 T. Fukuda, N. Kitamura and K. Tanie consideration to object dynamics. This can also be shown experiment-ally in comparison with conventional methods of constant feedback gain.

Keywords

Force Control Feedback Gain Hard Object Soft Object Gripper System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Hermes, Paris 1987

Authors and Affiliations

  • T. Fukuda
    • 1
    • 2
  • N. Kitamura
    • 1
  • K. Tanie
    • 2
  1. 1.The Science University of TokyoJapan
  2. 2.Mechanical Engineering LaboratoryMinistry of International Trade of IndustryJapan

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