Collecting a Swarm in a Grid Environment Using Shared, Global Inputs
This addresses the challenge of targeted drug delivery in healthcare, where micro-scale particles must be concentrated at a goal location, but it appears incremental as it builds on existing swarm control methods in grid settings.
The paper tackles the problem of collecting an under-actuated particle swarm in a grid environment with obstacles, using shared global inputs, and provides algorithms that achieve this with comparisons based on efficiency and implementation time.
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.