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Realizing whole-body tactile interactions with a self-organizing, multi-modal artificial skin on a humanoid robot

机译:在类人机器人上利用自组织多模式人造皮肤实现全身触觉交互

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In this paper, we present a new approach to realize whole-body tactile interactions with a self-organizing, multi-modal artificial skin on a humanoid robot. We, therefore, equipped the whole upper body of the humanoid HRP-2 with various patches of CellulARSkin - a modular artificial skin. In order to automatically handle a potentially high number of tactile sensor cells and motors units, the robot uses open-loop exploration motions, and distributed accelerometers in the artificial skin cells, to acquire its self-centered sensory-motor knowledge. This body self-knowledge is then utilized to transfer multi-modal tactile stimulations into reactive body motions. Tactile events provide feedback on changes of contact on the whole-body surface. We demonstrate the feasibility of our approach on a humanoid, here HRP-2, grasping large and unknown objects only via tactile feedback. Kinesthetically taught grasping trajectories, are reactively adapted to the size and stiffness of different test objects. Our paper contributes the first realization of a self-organizing tactile sensor-behavior mapping on a full-sized humanoid robot, enabling a position controlled robot to compliantly handle objects.
机译:在本文中,我们提出了一种新方法,可在人形机器人上实现具有自组织,多模式人工皮肤的全身触觉交互。因此,我们为人形HRP-2的整个上身配备了CellulARSkin的各种贴剂-一种模块化的人造皮肤。为了自动处理可能大量的触觉传感器单元和电机单元,该机器人使用开环探索运动和人造皮肤单元中的分布式加速度计来获取其以自我为中心的感觉运动知识。然后,利用这种身体的自我知识将多模式触觉刺激转化为反应性身体运动。触觉事件提供有关全身表面接触变化的反馈。我们展示了我们的方法在类人动物(此处为HRP-2)上的可行性,该类人动物只能通过触觉反馈来捕获大型未知物体。从运动学角度讲授的抓取轨迹,可以适应不同测试对象的大小和刚度。我们的论文为全尺寸人形机器人上自组织触觉传感器行为映射的首次实现做出了贡献,从而使位置控制机器人能够顺应性地处理物体。

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