Content area

Abstract

Cyborg insects refer to hybrid robots that integrate living insects with miniature electronic controllers to enable robotic-like programmable control. These creatures exhibit advantages over conventional robots in adaption to complex terrain and sustained energy efficiency. Nevertheless, there is a lack of literature on the control of multi-cyborg systems. This research gap is due to the difficulty in coordinating the movements of a cyborg system under the presence of insects' inherent individual variability in their reactions to control input. Regarding this issue, we propose a swarm navigation algorithm and verify it under experiments. This research advances swarm robotics by integrating biological organisms with control theory to develop intelligent autonomous systems for real-world applications.

Details

1009240
Title
Swarm navigation of cyborg-insects in unknown obstructed soft terrain
Publication title
arXiv.org; Ithaca
Publication year
2024
Publication date
Dec 21, 2024
Section
Computer Science; Electrical Engineering and Systems Science; Nonlinear Sciences
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2024-12-24
Milestone dates
2024-03-26 (Submission v1); 2024-03-27 (Submission v2); 2024-12-21 (Submission v3)
Publication history
 
 
   First posting date
24 Dec 2024
ProQuest document ID
3014699686
Document URL
https://www.proquest.com/working-papers/swarm-navigation-cyborg-insects-unknown/docview/3014699686/se-2?accountid=208611
Full text outside of ProQuest
Copyright
© 2024. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2024-12-25
Database
2 databases
  • ProQuest One Academic
  • ProQuest One Academic