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Found 6 papers, 0 papers with code
Backstepping Mean-Field Density Control for Large-Scale Heterogeneous Nonlinear Stochastic Systems
In this work, we present a backstepping design algorithm that extends density control to heterogeneous and higher-order stochastic systems in strict-feedback forms.
Distributed Mean-Field Density Estimation for Large-Scale Systems
This work studies how to estimate the mean-field density of large-scale systems in a distributed manner.
Feedback Interconnected Mean-Field Density Estimation and Control
Specifically, we propose new density control laws which use the mean-field density and its gradient as feedback, and prove that they are globally input-to-state stable (ISS) with respect to estimation errors.
Field Estimation using Robotic Swarms through Bayesian Regression and Mean-Field Feedback
Recent years have seen an increased interest in using mean-field density based modelling and control strategy for deploying robotic swarms.
Distributed Density Filtering for Large-Scale Systems Using Mean-Filed Models
In this work, we further study how to decentralize the density filter such that each agent can estimate the global density only based on its local observation and communication with neighbors.
Transporting Robotic Swarms via Mean-Field Feedback Control
With the rapid development of AI and robotics, transporting a large swarm of networked robots has foreseeable applications in the near future.
