Density Stabilization Strategies for Nonholonomic Agents on Compact Manifolds

• Published in: IEEE transactions on automatic control 2024-03, Vol.69 (3), p.1-16
• Main Authors: Elamvazhuthi, Karthik, Berman, Spring
• Format: Article
• Language: English
• Subjects: Control systems; Control theory; Controllability; Density; Ellipticity; Feedback control; Hypoelliptic operators; Manifolds; Markov processes; Mathematical models; mean-field control; multi-agent systems; nonholonomic systems; Partial differential equations; Probability theory; Reagents; Resource management; Robot control; Robotics; Robots; semilinear PDE; Stabilization; State feedback; Stochastic models; Stochastic processes; swarms; Switches; Switching; Task analysis
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/TAC.2023.3326060

In this article, we consider the problem of stabilizing a class of degenerate stochastic processes, which are constrained to a bounded Euclidean domain or a compact smooth manifold, to a given target probability density. This stabilization problem arises in the field of swarm robotics, for example in applications where a swarm of robots is required to cover an area according to a target probability density. Most existing works on modeling and control of robotic swarms that use partial differential equation (PDE) models assume that the robots' dynamics are holonomic, and hence, the associated stochastic processes have generators that are elliptic. We relax this assumption on the ellipticity of the generator of the stochastic processes, and consider the more practical case of the stabilization problem for a swarm of agents whose dynamics are given by a controllable driftless control-affine system. We construct state- feedback control laws that exponentially stabilize a swarm of nonholonomic agents to a target probability density that is sufficiently regular. State- feedback laws can stabilize a swarm only to target probability densities that are positive everywhere. To stabilize the swarm to probability densities that possibly have disconnected supports, we introduce a semilinear PDE model of a collection of interacting agents governed by a hybrid switching diffusion process. The interaction between the agents is modeled using a (mean-field) feedback law that is a function of the local density of the swarm, with the switching parameters as the control inputs. We show that under the action of this feedback law, the semilinear PDE system is globally asymptotically stable about the given target probability density. The stabilization strategies with and without agent interactions are verified numerically for agents that evolve according to the Brockett integrator; the strategy with interactions is additionally verified for agents that evolve according to an underactuated system on the sphere S^{2}.