Soft modularized robotic arm for safe human–robot interaction based on visual and proprioceptive feedback

Subyeong Ku, Byung-Hyun Song, Taejun Park, Younghoon Lee, Yong-Lae Park
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Abstract

This study proposes a modularized soft robotic arm with integrated sensing of human touches for physical human–robot interactions. The proposed robotic arm is constructed by connecting multiple soft manipulator modules, each of which consists of three bellow-type soft actuators, pneumatic valves, and an on-board sensing and control circuit. By employing stereolithography three-dimensional (3D) printing technique, the bellow actuator is capable of incorporating embedded organogel channels in the thin wall of its body that are used for detecting human touches. The organogel thus serves as a soft interface for recognizing the intentions of the human operators, enabling the robot to interact with them while generating desired motions of the manipulator. In addition to the touch sensors, each manipulator module has compact, soft string sensors for detecting the displacements of the bellow actuators. When combined with an inertial measurement unit (IMU), the manipulator module has a capability of estimating its own pose or orientation internally. We also propose a localization method that allows us to estimate the location of the manipulator module and to acquire the 3D information of the target point in an uncontrolled environment. The proposed method uses only a single depth camera combined with a deep learning model and is thus much simpler than those of conventional motion capture systems that usually require multiple cameras in a controlled environment. Using the feedback information from the internal sensors and camera, we implemented closed-loop control algorithms to carry out tasks of reaching and grasping objects. The manipulator module shows structural robustness and the performance reliability over 5,000 cycles of repeated actuation. It shows a steady-state error and a standard deviation of 0.8 mm and 0.3 mm, respectively, using the proposed localization method and the string sensor data. We demonstrate an application example of human–robot interaction that uses human touches as triggers to pick up and manipulate target objects. The proposed soft robotic arm can be easily installed in a variety of human workspaces, since it has the ability to interact safely with humans, eliminating the need for strict control of the environments for visual perception. We believe that the proposed system has the potential to integrate soft robots into our daily lives.
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基于视觉和本体感觉反馈的安全人机交互软模块化机械臂
本研究提出了一种模块化软机械臂,该机械臂集成了对人类触碰的感知功能,可实现人与机器人的物理交互。拟议的机械臂由多个软机械手模块连接而成,每个模块由三个波纹管型软驱动器、气动阀和板载传感与控制电路组成。通过采用立体光刻三维(3D)打印技术,波纹管执行器能够在其薄壁上嵌入有机凝胶通道,用于检测人体触摸。因此,有机凝胶可作为识别人类操作者意图的软接口,使机器人能够与他们互动,同时产生所需的机械手运动。除触摸传感器外,每个机械手模块还配有用于检测波纹管执行器位移的紧凑型软绳传感器。当与惯性测量单元(IMU)结合使用时,操纵器模块能够在内部估计自身的姿态或方向。我们还提出了一种定位方法,可以在不受控制的环境中估计操纵器模块的位置并获取目标点的三维信息。与通常需要在受控环境中使用多个摄像头的传统动作捕捉系统相比,我们提出的方法只使用了一个深度摄像头和一个深度学习模型,因此要简单得多。利用来自内部传感器和摄像头的反馈信息,我们实现了闭环控制算法,以执行伸手抓取物体的任务。机械手模块在重复执行 5000 个周期后显示出结构的鲁棒性和性能的可靠性。使用建议的定位方法和字符串传感器数据,它的稳态误差和标准偏差分别为 0.8 毫米和 0.3 毫米。我们展示了一个人机交互的应用实例,它利用人类的触摸作为触发器来拾取和操纵目标物体。由于拟议的软机械臂具有与人类安全互动的能力,无需严格控制视觉感知环境,因此可以轻松安装在各种人类工作空间。我们相信,拟议的系统有可能将软机器人融入我们的日常生活。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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Scaling effects of manufacturing processes and actuation sources on control of remotely powered micro actuators Soft modularized robotic arm for safe human–robot interaction based on visual and proprioceptive feedback
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