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1. Reconfigurable Innervation of Modular Soft Machines via Soft, Sticky, and Instant Electronic Adhesive Interlocking

Author

Jaeyoung Yoon, Junghwan Byun, Minjo Park, Hayun Kim, Woongbae Kim, Jinsu Yoon, Kyu-Jin Cho, and Yongtaek Hong

Subjects
adhesive interlocking, modular soft electronics, modular soft robot, reconfigurable robot, soft modular assembly, Computer engineering. Computer hardware, TK7885-7895, Control engineering systems. Automatic machinery (General), TJ212-225
Abstract

Adaptive and extreme changes in shape and configuration are the functional and morphological uniqueness of soft robots, but existing design approaches still rely on the predefined coordination of their “muscle” and “nerve” functions to produce such behaviors. Herein, a strategy is introduced for building modular soft machines that can be innervated in ways that conform to their body extension or shape changes, based on modular soft electronics. The development of soft electronic adhesive interlocking (SEAL) technology allows for instant, robust, and repeatable integration of soft electronic modules that can “innervate” and activate modular soft actuators and machines in a reconfigurable manner. Demonstrations of soft robotic tentacles and their grasping capability show that the robot function can be adapted to or reconfigured within the body with a length extended more than 10 times. The modular strategy presented herein can offer a unique promise to build up future robots with dynamic, reconfigurable functions.

Published
2023
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2. Compliant Suction Gripper with Seamless Deployment and Retraction for Robust Picking against Depth and Tilt Errors

Author

Yuna Yoo, Jaemin Eom, MinJo Park, and Kyu-Jin Cho

Subjects
FOS: Computer and information sciences, Human-Computer Interaction, Computer Science - Robotics, Control and Optimization, Artificial Intelligence, Control and Systems Engineering, Mechanical Engineering, Biomedical Engineering, Computer Vision and Pattern Recognition, Robotics (cs.RO), Computer Science Applications
Abstract

Applying suction grippers in unstructured environments is a challenging task because of depth and tilt errors in vision systems, requiring additional costs in elaborate sensing and control. To reduce additional costs, suction grippers with compliant bodies or mechanisms have been proposed; however, their bulkiness and limited allowable error hinder their use in complex environments with large errors. Here, we propose a compact suction gripper that can pick objects over a wide range of distances and tilt angles without elaborate sensing and control. The spring-inserted gripper body deploys and conforms to distant and tilted objects until the suction cup completely seals with the object and retracts immediately after, while holding the object. This seamless deployment and retraction is enabled by connecting the gripper body and suction cup to the same vacuum source, which couples the vacuum picking and retraction of the gripper body. Experimental results validated that the proposed gripper can pick objects within 79 mm, which is 1.4 times the initial length, and can pick objects with tilt angles up to 60{\deg}. The feasibility of the gripper was verified by demonstrations, including picking objects of different heights from the same picking height and the bin picking of transparent objects., Comment: 8 pages, 11 figures

Published
2022

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