Increasing the Reliability and Versatility of Jellyfish Biohybrid Vehicles via Species Selection and Rhopalia Removal
Document Type
Article
Publication Title
Biomimetics
Publication Date
12-1-2025
Abstract
Jellyfish biohybrid robots have been demonstrated to be successfully programmed to perform vertical sampling profiles of the ocean water column. However, the jellyfish’s endogenous swimming behavior can interfere with the controlled swim cycles, decreasing performance. Further, the model animal used to date, Aurelia aurita, is a relatively slow, weakly swimming species. To enhance the performance of the biohybrid vehicles, we tested whether removing the swimming pacemaker of the jellyfish, the rhopalia, eliminated endogenous movements and enhanced responsiveness of the jellyfish to the swim controller. Further, we tested the responsiveness of two fast-swimming jellyfish species, the rhizostome Cassiopea spp. and the cubomedusae Alatina alata. We found in field trials, where the jellyfish swam controlled vertical profiles in the ocean, that removal of rhopalia eliminated all endogenous behaviors and greatly improved the responsiveness of the jellyfish to the swim controller. This was especially true for species with strong endogenous behaviors that prevented the controller from manipulating swim pulses. Further, we found that both Cassiopea spp. and A. alata were highly responsive to the swim controller and that these faster-swimming jellyfish species greatly increased the speed at which the biohybrid vehicle could traverse vertical profiles in the water column. These enhancements greatly increase the reliability and versatility of jellyfish biohybrid robot vehicles.
Volume
10
Issue
12
DOI
10.3390/biomimetics10120810
Recommended Citation
Anuszczyk, S., Yoder, N., Costello, J., Dabiri, J., Gemmell, B., Rutledge, K., & Colin, S. (2025). Increasing the Reliability and Versatility of Jellyfish Biohybrid Vehicles via Species Selection and Rhopalia Removal. Biomimetics, 10 (12) https://doi.org/10.3390/biomimetics10120810
E-ISSN
23137673
