Publications

2024

G. Amorim, A. Bizyaeva, A. Franci, and N. E. Leonard

Spatially-invariant opinion-dynamics on the circle

IEEE Control Systems Letters, vol. 8, pp. 3231–3236, 2024. Presented at ACC 2025.

We propose and analyze a nonlinear opinion dynamics model for an agent making decisions about a continuous distribution of options in the presence of input. Inspired by perceptual decision-making, we develop new theory for opinion formation in response to inputs about options distributed on the circle. Options on the circle can represent, e.g., the possible directions of perceived objects and resulting heading directions in planar robotic navigation problems. Interactions among options are encoded through a spatially invariant kernel, which we design to ensure that only a small (finite) subset of options can be favored over the continuum. We leverage the spatial invariance of the model linearization to design flexible, distributed opinion-forming behaviors using spatiotemporal frequency domain and bifurcation analysis. We illustrate our model’s versatility with an application to robotic navigation in crowded spaces.

G. Amorim, M. Santos, S. Park, A. Franci, and N. E. Leonard

Threshold decision-making dynamics adaptive to physical constraints and changing environment

European Control Conference (ECC), 2024.

We propose a threshold decision-making frame-work for controlling the physical dynamics of an agent switching between two spatial tasks. Our framework couples a nonlinear opinion dynamics model that represents the evolution of an agent's preference for a particular task with the physical dynamics of the agent. We prove the bifurcation that governs the behavior of the coupled dynamics. We show by means of the bifurcation behavior how the coupled dynamics are adaptive to the physical constraints of the agent. We also show how the bifurcation can be modulated to allow the agent to switch tasks based on thresholds adaptive to environmental conditions. We illustrate the benefits of the approach through a multi-robot task allocation application for trash collection.

2022

A. Bizyaeva, G. Amorim, M. Santos, A. Franci, and N. E. Leonard

Switching transformations for decentralized control of opinion patterns in signed networks: application to dynamic task allocation

IEEE Control Systems Letters, vol. 6, pp. 3463–3468, 2022.

We propose a new decentralized design to control opinion patterns on signed networks of agents making decisions about two options and to switch the network from any opinion pattern to a new desired one. Our method relies on switching transformations, which switch the sign of an agent’s opinion at a stable equilibrium by flipping the sign of the interactions with its neighbors. The global dynamical behavior of the switched network can be predicted rigorously when the original, and thus the switched, networks are structurally balanced. Structural balance ensures that the network dynamics are monotone, which makes the study of the basin of attraction of the various opinion patterns amenable to monotone systems theory. We illustrate the utility of the approach through scenarios motivated by multi-robot coordination and dynamic task allocation.

@article{Bizyaeva2022Switching,
  author  = {Bizyaeva, Anastasia and Amorim, Giovanna and Santos, M. and Franci, Alessio and Leonard, Naomi E.},
  title   = {Switching transformations for decentralized control of opinion patterns in signed networks: application to dynamic task allocation},
  journal = {IEEE Control Systems Letters},
  volume  = {6},
  pages   = {3463--3468},
  year    = {2022}
}