{"ID":2823741,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.24886","arxiv_id":"2512.24886","title":"Heterogeneous Multi-Agent Multi-Target Tracking using Cellular Sheaves","abstract":"Multi-agent target tracking in the presence of nonlinear dynamics and agent heterogeneity, where state-space dimensions may differ, is a challenging problem that traditional graph Laplacian methods cannot easily address. This work leverages the framework of cellular sheaves, a mathematical generalization of graph theory, to natively model such heterogeneous systems. While existing coordination sheaf frameworks focus on cooperative problems like consensus, this work extends them to the non-cooperative target-tracking problem. The tracking of multiple, unknown targets is formulated as a harmonic extension problem on a cellular sheaf, accommodating nonlinear dynamics and external disturbances for all agents. A decentralized control law is developed using the sheaf Laplacian, and a corresponding Lyapunov-based stability analysis is provided to guarantee tracking error convergence, with results validated by simulation.","short_abstract":"Multi-agent target tracking in the presence of nonlinear dynamics and agent heterogeneity, where state-space dimensions may differ, is a challenging problem that traditional graph Laplacian methods cannot easily address. This work leverages the framework of cellular sheaves, a mathematical generalization of graph theor...","url_abs":"https://arxiv.org/abs/2512.24886","url_pdf":"https://arxiv.org/pdf/2512.24886v1","authors":"[\"Tyler Hanks\",\"Cristian F. Nino\",\"Joana Bou Barcelo\",\"Austin Copeland\",\"Warren Dixon\",\"James Fairbanks\"]","published":"2025-12-31T14:29:44Z","proceeding":"eess.SY","tasks":"[\"eess.SY\",\"cs.MA\",\"math.AT\"]","methods":"[]","has_code":false}