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Soft Robot 2022 May 11. Epub 2022 May 11.

Department of Mechanical Engineering, National Taiwan University, Taipei, Taiwan.

Pipe inspection and maintenance are necessary to prevent economic and casualty losses due to leakage of fluids from damaged pipes. In-pipe soft robots made of highly deformable materials have been proposed to meet the needs, yet most of those comprise multiple segments and require multiple actuators controlled independently, resulting in less compact structures and more demanding control schemes. In this study, we harness the highly nonlinear buckling of elastic ribbons and bioinspired artificial muscles to significantly enhance the crawling capability of a single-actuator soft robot. Read More

Microsyst Nanoeng 2022 31;8:37. Epub 2022 Mar 31.

State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, 610054 People's Republic of China.

Origami has become an optimal methodological choice for creating complex three-dimensional (3D) structures and soft robots. The simple and low-cost origami-inspired folding assembly provides a new method for developing 3D soft robots, which is ideal for future intelligent robotic systems. Here, we present a series of materials, structural designs, and fabrication methods for developing independent, electrically controlled origami 3D soft robots for walking and soft manipulators. Read More

ACS Appl Mater Interfaces 2022 May 20;14(17):20291-20302. Epub 2022 Apr 20.

State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, China.

The systematicness, flexibility, and complexity of natural biological organisms are a constant stream of inspiration for researchers. Therefore, mimicking the natural intelligence system to develop microrobotics has attracted broad interests. However, developing a multifunctional device for various application scenarios has great challenges. Read More

Adv Intell Syst 2021 Sep 26;3(9). Epub 2021 Jun 26.

Department of Mechanical Engineering, University of Utah, Salt Lake City, UT 84112, USA.

Reinforcement learning control methods can impart robots with the ability to discover effective behavior, reducing their modeling and sensing requirements, and enabling their ability to adapt to environmental changes. However, it remains challenging for a robot to achieve navigation in confined and dynamic environments, which are characteristic of a broad range of biomedical applications, such as endoscopy with ingestible electronics. Herein, a compact, 3D-printed three-linked-sphere robot synergistically integrated with a reinforcement learning algorithm that can perform adaptable, autonomous crawling in a confined channel is demonstrated. Read More

Sci Adv 2022 Apr 30;8(13):eabm7834. Epub 2022 Mar 30.

Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA.

Biomimetic soft robotic crawlers have attracted extensive attention in various engineering fields, owing to their adaptivity to different terrains. Earthworm-like crawlers realize locomotion through in-plane contraction, while inchworm-like crawlers exhibit out-of-plane bending-based motions. Although in-plane contraction crawlers demonstrate effective motion in confined spaces, miniaturization is challenging because of limited actuation methods and complex structures. Read More