Abstract
In nature, cells combine into different structures to perform required tasks and can break and rejoin to make smaller and larger organisms. Taking inspiration from cells, we present an adaptive soft robot composed of simple modular elements (cells) in a linear arrangement, joined together by magnets, capable of performing locomotion by exploiting frictional asymmetries with the terrain. Using a simple control mechanism to change their volumetric actuation, a travelling wave was generated to move the robot. Based on the inflation profile of the cell, we defined 4 geometric states, S1 (contracted), S2 (relaxed state), S3 (intermediate state) and S4 (inflated). In locomotion gaits, each cell can act as a foot or a muscle, depending on degree of inflation, and change function throughout the gait. The modular robot can also separate itself into multiple parts and recombine as needed, demonstrating attractive capabilities for autonomous exploration in natural environments. This can potentially be used to remove damaged cells or change the shape of the robot body. We present the design of the modular soft robot and demonstrate its locomotion and reconfiguration capabilities.
Original language | English |
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Title of host publication | 2023 IEEE International Conference on Soft Robotics, RoboSoft 2023 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
ISBN (Electronic) | 9798350332223 |
DOIs | |
Publication status | Published - 2023 |
Event | 2023 IEEE International Conference on Soft Robotics, RoboSoft 2023 - Singapore, Singapore Duration: 3 Apr 2023 → 7 Apr 2023 |
Publication series
Name | 2023 IEEE International Conference on Soft Robotics, RoboSoft 2023 |
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Conference
Conference | 2023 IEEE International Conference on Soft Robotics, RoboSoft 2023 |
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Country/Territory | Singapore |
City | Singapore |
Period | 3/04/23 → 7/04/23 |
Bibliographical note
Funding Information:email: [email protected] 1Department of Aerospace Engineering, University of Bristol, UK 2Department of Engineering Mathematics, University of Bristol, UK 3SoftLab, Bristol Robotics Laboratory, University of Bristol and University of the West of England, UK RB and HH were supported by the Engineering and Physical Sciences Research Council (EPSRC) grant EP/L015293/1. JR is also supported by EP-SRC grants EP/V062158/1, EP/S021795/1, EP/R02961X/1, EP/V026518/1, and EP/T020792/1, and the Royal Academy of Engineering through the Chair in Emerging Technologies scheme. Data are available at the University of Bristol data repository, data.bris, at https://doi.org/10.5523/bris.2xnkxqqa7r5cc2rwdauepmqkdq
Publisher Copyright:
© 2023 IEEE.