Navigation of Robotic Swarmalators With Dynamics and Constraints

Abstract

Swarmalator studies have enabled self-organized collective behaviors that emerge from dual spatial and temporal coupling, without relying on external inputs. These behaviors arise solely from attractive and repulsive interactions modulated by a few global parameters. Here, we treat the swarmalator model as a planner and study how several of the collective behaviors change in terms of space-phase organization when the agents are robots with vehicle dynamics and constraints: including omnidirectional, unicycle, and bicycle dynamics. Furthermore, we use the control barrier function method to guarantee that the collective can navigate around objects, through cluttered environments, and transport objects in between obstacles by exploiting global and local control methods. This work brings us closer to realizing large groups of robotic swarmalators, of heterogeneous dynamics, that can enable shape formation, navigation, and object manipulation in cluttered environments.