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Effect of base rotation on the controllability of a redundant soft robotic arm

机译:基础旋转对冗余软机器人手臂可控制性的影响

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摘要

Soft robotic arms have gained popularity in the recent years because of their dexterity, robustness and safe interaction with humans. However, since these arms are subject to non-linear mechanics and are intrinsically under-actuated, their control still present many challenges. Octopus arms are one of the most popular biological models for soft robotics. It is known that the octopus reaching movement consists in two steps: (1) the rotation of the arm's base towards the target, and (2) the extension of the arm to reach the target. From a robotics point of view, the rotation of the base adds one additional degree of freedom to an already hyper-redundant system. Therefore, its role in the effectiveness of the control is ambiguous. In this work, we investigate the role of the base rotation for learning an effective reaching strategy. We conduct numerical experiments based on a mathematical model of the mechanics of the octopus arm in water and a simple neural network enabling to encode the control strategy through optimization learning. The network node corresponding to the base rotation is switched on or off for comparison. We test the reaching success rate with and without base rotation with targets in various positions. The results show that the addition of the base rotation can be highly beneficial or even detrimental, based on the position of the target. Nonetheless, globally the addition of base rotation affects the control strategy and expand the reachable regions.
机译:近年来,软机械臂因其灵巧,坚固且与人安全互动而广受欢迎。然而,由于这些臂受到非线性机械的影响并且本质上被致动不足,因此它们的控制仍然提出许多挑战。章鱼手臂是最流行的软机器人生物学模型之一。已知章鱼到达运动包括两个步骤:(1)手臂的基座朝向目标的旋转,以及(2)手臂的延伸以到达目标。从机器人的角度来看,基座的旋转为已经超冗余的系统增加了一个额外的自由度。因此,其在控制有效性中的作用是模棱两可的。在这项工作中,我们调查了基础轮换对于学习有效的到达策略的作用。我们基于章鱼臂在水中的力学数学模型和一个简单的神经网络进行数值实验,该网络能够通过优化学习对控制策略进行编码。与基础旋转相对应的网络节点被打开或关闭以进行比较。我们测试在有不同位置的目标的情况下是否进行基本旋转而达到的成功率。结果表明,基于目标的位置,基础旋转的添加可能非常有益甚至有害。但是,在全球范围内增加基本旋转会影响控制策略并扩展可触及区域。

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  • 来源
  • 会议地点 Livorno(IT)
  • 作者单位

    Department of Applied Physics, Graduate School of Science and Engineering, Waseda University, 3-4-1 Okubo Shinjuku-ku, Tokyo 169-8555, Japan;

    Institute of Microengineering Neuchâtel campus, School of Engineering, École Polytechnique Fédérale de Lausanne, Rue de la Maladière 71b, 2000 Neuchâtel, Switzerland;

    The BioRobotics Institute, Scuola Superiore Sant'Anna, Polo Sant'Anna Valdera, Viale Rinaldo Piaggio 34 56025 Pontedera (Pisa) Italy;

    Department of Applied Physics, Graduate School of Science and Engineering, Waseda University, 3-4-1 Okubo Shinjuku-ku, Tokyo 169-8555, Japan;

    Department of Applied Physics, Graduate School of Science and Engineering, Waseda University, 3-4-1 Okubo Shinjuku-ku, Tokyo 169-8555, Japan;

    The BioRobotics Institute, Scuola Superiore Sant'Anna, Polo Sant'Anna Valdera, Viale Rinaldo Piaggio 34 56025 Pontedera (Pisa) Italy;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Soft robotics; Optimization; Task analysis; Manipulators; Muscles; Genetic algorithms;

    机译:软机器人;优化;任务分析;操纵器;肌肉;遗传算法;;

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