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Collecting a swarm in a grid environment using shared, global inputs

Arun Mahadev, Dominik Krupke, Jan-Marc Reinhardt, Sándor P. Fekete, Aaron T. Becker

Year
2016
Citations
14

Abstract

This paper investigates efficient techniques to collect and concentrate an under-actuated particle swarm despite obstacles. Concentrating a swarm of particles is of critical importance in health-care for targeted drug delivery, where micro-scale particles must be steered to a goal location. Individual particles must be small in order to navigate through micro-vasculature, but decreasing size brings new challenges. Individual particles are too small to contain on-board power or computation and are instead controlled by a global input, such as an applied fluidic flow or electric field. To make progress, this paper considers a swarm of robots initialized in a grid world in which each position is either free-space or obstacle. This paper provides algorithms that collect all the robots to one position and compares these algorithms on the basis of efficiency and implementation time.

Keywords

Swarm behaviourComputer scienceGridDistributed computingParticle swarm optimizationComputationPosition (finance)ObstacleSwarm roboticsRobot

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