Electric Field Control of Bacteria-Powered Microrobots Using a Static Obstacle Avoidance Algorithm

A bacteria-powered microrobot (BPM) is a hybrid robotic system consisting of an SU-8 microstructure with active surfaces or bacterial carpets, in which massive arrays of biomolecular flagellar motors work cooperatively. This paper suggests an obstacle-avoidance method based on a BPM's response...

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Bibliographic Details
Published inIEEE transactions on robotics Vol. 32; no. 1; pp. 125 - 137
Main Authors Kim, Hoyeon, Kim, Min Jun
Format Journal Article
LanguageEnglish
Published New York IEEE 01.02.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Bacteria
Bacteria-powered microrobots (BPMs)
Collision avoidance
Electric fields
Force
Mathematical model
Microorganisms
Microstructure
motion plan
navigation
obstacle avoidance
Propulsion
Robots
Simulation
Software engineering
Bacteria-powered microrobots (BPMs)
obstacle avoidance
navigation
motion plan
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Summary:A bacteria-powered microrobot (BPM) is a hybrid robotic system consisting of an SU-8 microstructure with active surfaces or bacterial carpets, in which massive arrays of biomolecular flagellar motors work cooperatively. This paper suggests an obstacle-avoidance method based on a BPM's response to electric fields. The negatively charged bacteria enable the BPM to follow electric fields. In our previous demonstration of the single BPM controllability, we observed a vast change in the control dynamics when obstructions distorted the applied electric field and affected BPM steering and control. In this paper, we demonstrate an obstacle avoidance method that takes the electric field distortion into account to navigate a BPM through multiple static obstacles in real time. We used an artificial potential field and configuration space in our algorithm to generate an objective function for the electric field distortion and collision around/with obstacles, respectively. In addition, finite-element modeling through COMSOL Multiphysics engineering software was used to simulate charged-particle trajectories in a distorted electric field. Finally, we describe the feasibility of our proposed obstacle avoidance approach through experiments and compared these data with simulation results.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:1552-3098
1941-0468
DOI:10.1109/TRO.2015.2504370