Steering Micro-Robotic Swarm by Dynamic Actuating Fields

Q. Chao, J Yu, C. Dai, T Xu, L. Zhang, Charlie Wang, X. Jin

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

4 Citations (Scopus)
29 Downloads (Pure)

Abstract

We present a general solution for steering microrobotic
swarm by dynamic actuating fields. In our approach, the
motion of micro-robots is controlled by changing the actuating
direction of a field applied to them. The time-series sequence
of actuating field’s directions can be computed automatically.
Given a target position in the domain of swarm, a governing
field is first constructed to provide optimal moving directions at
every points. Following these directions, a robot can be driven
to the target efficiently. However, when working with a crowd of
micro-robots, the optimal moving directions on different agents
can contradict with each other. To overcome this difficulty, we
develop a novel steering algorithm to compute a statistically
optimal actuating direction at each time frame. Following a
sequence of these actuating directions, a crowd of micro-robots
can be transported to the target region effectively. Our steering
strategy of swarm has been verified on a platform that generates
magnetic fields with unique actuating directions. Experimental
tests taken on aggregated magnetic micro-particles are quite
encouraging.
Original languageEnglish
Title of host publication2016 IEEE International Conference on Robotics and Automation
Place of PublicationPiscataway
PublisherIEEE Society
Pages5230-5235
Number of pages6
ISBN (Electronic)978-1-4673-8026-3
ISBN (Print)978-1-4673-8025-6
DOIs
Publication statusPublished - 2016
EventIEEE International Conference on Robotics and Automation (ICRA 2016) - Stockholm, Sweden
Duration: 16 May 201621 May 2016

Conference

ConferenceIEEE International Conference on Robotics and Automation (ICRA 2016)
CountrySweden
CityStockholm
Period16/05/1621/05/16

Keywords

  • microrobots
  • mobile robots
  • motion control
  • multi-robot systems
  • position control
  • time series

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