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Soft robot review

  • Special Issue: Soft Robotics
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International Journal of Control, Automation and Systems Aims and scope Submit manuscript

Abstract

Soft robots are often inspired from biological systems which consist of soft materials or are actuated by electrically activated materials. There are several advantages of soft robots compared to the conventional robots; safe human-machine interaction, adaptability to wearable devices, simple gripping system, and so on. Due to the unique features and advantages, soft robots have a considerable range of applications. This article reviews state-of-the-art researches on soft robots and application areas. Actuation systems for soft robots can be categorized and analyzed into three types: variable length tendon, fluidic actuation, and electro-active polymer (EAP). The deformable property of soft robots restricts the use of many conventional rigid sensors such as encoders, strain gauges, or inertial measurement units. Thus, contactless approaches for sensing and/or sensors with low modulus are preferable for soft robots. Sensors include low modulus (< 1 MPa) elastomers with liquid-phase material filled channels and are appropriate for proprioception which is determined by the degree of curvature. In control perspective, novel control idea should be developed because the conventional control techniques may be inadequate to handle soft robots. Several innovative techniques and diverse materials & fabrication methods are described in this review article. In addition, a wide range of soft robots are characterized and analyzed based on the following sub-categories; actuation, sensing, structure, control and electronics, materials, fabrication and system, and applications.

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Authors and Affiliations

  1. Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul, 03080, Korea

    Chiwon Lee

  2. Interdisciplinary Program for Bioengineering, Graduate School, Seoul National University, Seoul, 08826, Korea

    Myungjoon Kim, Yoon Jae Kim & Nhayoung Hong

  3. School of Mechanical and Aerospace Engineering, Seoul National University, Seoul, 151-742, Korea

    Seungwan Ryu & H. Jin Kim

  4. Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, 03080, Korea

    Sungwan Kim

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  1. Chiwon Lee
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  2. Myungjoon Kim
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Correspondence to Sungwan Kim.

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Recommended by Editor-in-Chief Young Hoon Joo. This work was supported by the Bio and Medical Technology Development Program of the NRF funded by the Korean Government, MSIP (NRF-2014M3A9E3064623), the Interdisciplinary Research Initiatives Program from College of Engineering and College of Medicine, Seoul National University (Grant No. 800-20160095), and the Research Program 2016 funded by Seoul National University College of Medicine Research Foundation (Grant No. 800-20160072). Chiwon Lee, Myungjoon Kim, Yoon Jae Kim, and Nhayoung Hong contributed equally to this work (co-first author).

Chiwon Lee received the B.S. degree in Mechanical & Aerospace Engineering and Ph.D. degree in the Interdisciplinary Program for Bioengineering from Seoul National University (SNU), in 2011 and 2015, respectively. He is a senior researcher with the Institute of Medical and Biological Engineering, SNU since Sept. 2015. He is currently conducting researches about medical robot, machine learning, and 3D printing technology for medical applications.

Myungjoon Kim received the B.S. degree in Electronics Engineering from Tsinghua University, Beijing China, in 2012. He is currently pursuing a Ph.D. degree in the Interdisciplinary Program for Bioengineering from Seoul National University, Seoul Korea. His main research area is development of medical robot system.

Yoon Jae Kim received the B.S. degree in Mechanical & Aerospace Engineering from Seoul National University in 2014. He is currently pursuing a Ph.D. degree in the Interdisciplinary Program for Bioengineering from Seoul National University, Seoul Korea. His main research interests include rehabilitation robots and biosignal processing.

Nhayoung Hong received the B.S. degree in Bio-Mechatronics from Sungkyunkwan University in 2016. She is currently pursuing a Ph.D. degree in the Interdisciplinary Program for Bioengineering from Seoul National University. Her research interests include surgical robots and biomedical control.

Seungwan Ryu received the B.S. degree in mechanical engineering from Hanyang University, Seoul, Korea, in 2013, and the M.S degree from Seoul National University, Seoul, Korea, in 2015. He is currently pursuing the Ph.D. degree in the Department of Mechanical and Aerospace Engineering at Seoul National University. His research interests include control of unmanned micro aerial vehicles and biomimetic mobile robots, and application of flapping wing mechanisms.

H. Jin Kim received her B.S. degree from Korean Advanced Institute of Technology in 1995, and M.S. and Ph.D. degrees from the University of California, Berkeley, USA, in 1999 and 2001, respectively, all in mechanical engineering. From 2002 to 2004, she was a postdoctoral researcher in Electrical Engineering and Computer Sciences at University of California, Berkeley. In 2004, she joined the School of Mechanical and Aerospace Engineering at Seoul National University, where she is currently a Professor. Her research interests are intelligent control of robotic systems, motion planning and vision-based navigation.

Sungwan Kim received his B.S. degree in Electronics Engineering and M.S. degree in Control & Instrumentation Engineering from Seoul National University (SNU), Seoul Korea in 1985 and 1987, and his Ph.D. degree in Electrical Engineering from University of California at Los Angeles in 1993, respectively. He is a professor with the Department of Biomedical Engineering, SNU College of Medicine since 2010. Prior to joining to the SNU, he worked as a Senior Aerospace Engineer at National Aeronautics and Space Administration (NASA) Langley Research Center, Hampton, Virginia, USA. He is an Associate Fellow of the AIAA and a Senior Member of the IEEE.

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Lee, C., Kim, M., Kim, Y.J. et al. Soft robot review. Int. J. Control Autom. Syst. 15, 3–15 (2017). https://doi.org/10.1007/s12555-016-0462-3

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