Journal article
Electric Field Control of Bacteria-Powered Microrobots Using a Static Obstacle Avoidance Algorithm
IEEE transactions on robotics, v 32(1), pp 125-137
01 Feb 2016
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
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.
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Details
- Title
- Electric Field Control of Bacteria-Powered Microrobots Using a Static Obstacle Avoidance Algorithm
- Creators
- Hoyeon Kim - Drexel UniversityMin Jun Kim - Drexel University
- Publication Details
- IEEE transactions on robotics, v 32(1), pp 125-137
- Publisher
- IEEE
- Number of pages
- 13
- Grant note
- 1306794 / National Science Foundation under DMR 10052980 / Korea Evaluation Institute of Industrial Technology - Ministry of Trade, Industry, and Energy under Grant MOTIE 1000255 / National Science Foundation under CMMI W911NF-11-1-0490 / Army Research Office
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Mechanical Engineering and Mechanics
- Web of Science ID
- WOS:000370764000009
- Scopus ID
- 2-s2.0-84962028322
- Other Identifier
- 991019173573104721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Robotics