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A robot leg with compliant tarsus and its neural control for efficient and adaptive locomotion on complex terrains

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Abstract

Insects, like dung beetles, show fascinating locomotor abilities. They can use their legs to walk on complex terrains (e.g., rocky and curved surfaces) and to manipulate objects. They also exploit their compliant tarsi, increasing the contact area between the legs and surface, to enhance locomotion, and object manipulation efficiency. Besides these biomechanical components, their neural control allows them to move at a proper frequency with respect to their biomechanical properties and to quickly adapt their movements to deal with environmental changes. Realizing these complex achievements on artificial systems remains a grand challenge. As a step towards this direction, we present here our first prototype of an artificial dung beetle-like leg with compliant tarsus by analyzing real dung beetle legs through \(\mu\)CT scans. Compliant tarsus was designed according to the so-called fin ray effect. Real robot experiments show that the leg with compliant tarsus can efficiently move on rocky and curved surfaces. We also apply neural control, based on a central pattern generator (CPG) circuit and synaptic plasticity, to autonomously generate a proper moving frequency of the leg. The controller can also adapt the leg movement to deal with environmental changes, like different treadmill speeds, within a few steps.

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Notes

  1. Although such a structure has been developed and employed as a gripper of robot arms for object manipulation (see MultiChoiceGripper of Festo at https://www.festo.com/bionik), it is here developed and employed as a robot foot for efficient locomotion.

  2. This tarsus has the same shape and size as the bio-inspired compliant tarsus but it lacks flexibility and compliance due to its structure.

  3. This CPG model will show chaotic dynamics if its synaptic weights are set to \(W_{00}=-5.5, W_{01}=1.48, W_{10}=-1.65, W_{11}=0.0\) with additional bias terms (\(B_0 = -5.73, B_1 = 0.25\)) projecting to the neurons \(H_0\) and \(H_1\), respectively. The chaotic pattern proves behaviorally useful for, e.g., self-untrapping from a hole in the ground [26].

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Acknowledgments

This research was supported by Center for BioRobotics (CBR) at University of Southern Denmark (SDU, Denmark) and the Scandinavian Guest Professorship program of Kiel University (CAU, Germany).

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    Authors and Affiliations

    1. Embodied AI and Neurorobotics Lab, Centre for BioRobotics, The Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, 5230, Odense, Denmark

      G. Di Canio, S. Stoyanov, J. C. Larsen & P. Manoonpong

    2. Centre for BioRobotics,The Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, 5230, Odense, Denmark

      J. Hallam

    3. Functional Morphology and Biomechanics, Zoological Institute, Kiel University, Kiel, 24118, Germany

      A. Kovalev, T. Kleinteich & S. N. Gorb

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    1. G. Di Canio
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    Correspondence to P. Manoonpong.

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    G. D. Canio and S. Stoyanov contributed equally to this work.

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    Canio, G.D., Stoyanov, S., Larsen, J.C. et al. A robot leg with compliant tarsus and its neural control for efficient and adaptive locomotion on complex terrains. Artif Life Robotics 21, 274–281 (2016). https://doi.org/10.1007/s10015-016-0296-3

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    • DOI: https://doi.org/10.1007/s10015-016-0296-3

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