SoftSAR: The New Softer Side of Socially Assistive Robots—Soft Robotics with Social Human–Robot Interaction Skills
Author:
Sun Yu-Chen, Effati Meysam, Naguib Hani E., Nejat GoldieORCID
Abstract
When we think of “soft” in terms of socially assistive robots (SARs), it is mainly in reference to the soft outer shells of these robots, ranging from robotic teddy bears to furry robot pets. However, soft robotics is a promising field that has not yet been leveraged by SAR design. Soft robotics is the incorporation of smart materials to achieve biomimetic motions, active deformations, and responsive sensing. By utilizing these distinctive characteristics, a new type of SAR can be developed that has the potential to be safer to interact with, more flexible, and uniquely uses novel interaction modes (colors/shapes) to engage in a heighted human–robot interaction. In this perspective article, we coin this new collaborative research area as SoftSAR. We provide extensive discussions on just how soft robotics can be utilized to positively impact SARs, from their actuation mechanisms to the sensory designs, and how valuable they will be in informing future SAR design and applications. With extensive discussions on the fundamental mechanisms of soft robotic technologies, we outline a number of key SAR research areas that can benefit from using unique soft robotic mechanisms, which will result in the creation of the new field of SoftSAR.
Funder
Age-Well Inc. Natural Sciences and Engineering Research Council Canada Research Chairs
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference156 articles.
1. Schneier, M., Schneier, M., and Bostelman, R. (2015). Literature Review of Mobile Robots for Manufacturing, US Department of Commerce, National Institute of Standards and Technology. 2. Nonami, K., Kendoul, F., Suzuki, S., Wang, W., and Nakazawa, D. (2010). Autonomous Flying Robots: Unmanned Aerial Vehicles and Micro Aerial Vehicles, Springer Science & Business Media. 3. Hebert, M.H., Thorpe, C.E., and Stentz, A. (2012). Intelligent Unmanned Ground Vehicles: Autonomous Navigation Research at Carnegie Mellon, Springer Science & Business Media. 4. Zhang, J., Lyu, Y., Roppel, T., Patton, J., and Senthilkumar, C. (2016, January 14–17). Mobile Robot for Retail Inventory Using RFID. Proceedings of the 2016 IEEE international conference on Industrial technology (ICIT), Taipei, Taiwan. 5. Kyrarini, M., Lygerakis, F., Rajavenkatanarayanan, A., Sevastopoulos, C., Nambiappan, H.R., Chaitanya, K.K., Babu, A.R., Mathew, J., and Makedon, F. (2021). A survey of robots in healthcare. Technologies, 9.
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