Automated Control of Multifunctional Magnetic Spores Using Fluorescence Imaging for Microrobotic Cargo Delivery
Refereed conference paper presented and published in conference proceedings


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AbstractMicrorobotic cargo delivery possesses promising perspective for precision medicine, and has attracted much attention recently. However, its automation remains challenging, especially with complex environmental conditions, such as obstacles and obstructed optical feedback. In this paper, we propose an automated control approach for a new microrobotic cargo carrier, i.e. the multifunctional magnetic spore (MagSpore). By surface functionalization of the spore with Fe3O4 nanoparticles and carbon quantum dots, it can be remotely actuated and tracked by an electromagnetic coil system and the fluorescence microscopy, respectively. Our strategy utilizes fluorescence imaging for vision feedback, which enhances the recognition and tracking of Mag-Spores and cells. Then, information of the cells and Mag-Spores for planning and control is identified via image processing, and an optimal path planner with obstacle avoidance capability is designed based on the Particle Swarm Optimization (PSO) algorithm. To make the Mag-Spore follow the planed path accurately, an observer-based trajectory tracking controller is synthesized. Simulations and experiments are conducted to demonstrate the effectiveness of the proposed control approach.
All Author(s) ListLidong Yang, Yabin Zhang, Chi Ian Vong, Li Zhang
Name of Conference25th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Start Date of Conference01/10/2018
End Date of Conference05/10/2018
Place of ConferenceMadrid
Country/Region of ConferenceSpain
Journal name2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
Proceedings TitleIEEE International Conference on Intelligent Robots and Systems
Title of Publication2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
Year2018
PublisherIEEE
Pages6180 - 6185
ISBN978-1-5386-8094-0
ISSN2153-0858
LanguagesEnglish-United Kingdom
Web of Science Subject CategoriesComputer Science, Artificial Intelligence;Computer Science, Information Systems;Robotics;Computer Science;Robotics

Last updated on 2020-02-06 at 01:33