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Behavioristic image-based pose control of mobile manipulators using an uncalibrated eye-in-hand vision system

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Abstract

In the execution of material handling, the mobile manipulator is controlled to reach a station by its mobile base. This study adopts an uncalibrated eye-in-hand vision system to provide visual information for the manipulator to pick up a workpiece on the station. A novel vision-guided control strategy with a behavior-based look-and-move structure is proposed. This strategy is based on six image features, predefined by image moment method. In the designed neural-fuzzy controllers with varying learning rate, each image feature error is taken to generate intuitively one DOF motion command relative to the camera coordinate frame using fuzzy rules, which define a particular visual behavior. These behaviors are then fused to produce a final command action to perform grasping tasks using the proposed behavior fusion scheme. Finally, the proposed control strategy is experimentally applied to control the end-effector to approach and grasp a workpiece in various locations on a station.

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Acknowledgements

The authors would like to thank the National Science Council of the Republic of China, for financially supporting this research under Contract No. NSC 102-2221-E-006-295.

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Authors and Affiliations

  1. National Cheng Kung University, Tainan, Taiwan

    Tsing-Iuan James Tsay & Pei-Jiun Hung

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  1. Tsing-Iuan James Tsay
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  2. Pei-Jiun Hung
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Correspondence to Tsing-Iuan James Tsay.

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Tsay, TI.J., Hung, PJ. Behavioristic image-based pose control of mobile manipulators using an uncalibrated eye-in-hand vision system. Artif Life Robotics 23, 94–102 (2018). https://doi.org/10.1007/s10015-017-0399-5

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  • DOI: https://doi.org/10.1007/s10015-017-0399-5

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