Algorithms For Shaping a Particle Swarm With a Shared Control Input Using Boundary Interaction
This addresses the limited configuration range for micro- and nano-robots controlled globally, offering incremental improvements in swarm manipulation.
The paper tackles the problem of shaping particle swarms with shared control inputs by using boundary interactions, achieving algorithms to place robots at arbitrary locations and control swarm covariance, validated with simulations and hardware using 100 robots.
Consider a swarm of particles controlled by global inputs. This paper presents algorithms for shaping such swarms in 2D using boundary walls. The range of configurations created by conforming a swarm to a boundary wall is limited. We describe the set of stable configurations of a swarm in two canonical workspaces, a circle and a square. To increase the diversity of configurations, we add boundary interaction to our model. We provide algorithms using friction with walls to place two robots at arbitrary locations in a rectangular workspace. Next, we extend this algorithm to place $n$ agents at desired locations. We conclude with efficient techniques to control the covariance of a swarm not possible without wall-friction. Simulations and hardware implementations with 100 robots validate these results. These methods may have particular relevance for current micro- and nano-robots controlled by global inputs.