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The envisioned robotic aerial base station (RABS) concept is expected tobring further flexibility to integrated sensing and communication (ISAC)systems. In this letter, characterizing the spatial traffic distribution on agrid-based model, the RABS-assisted ISAC system is formulated as a robustoptimization problem to maximize the minimum satisfaction rate (SR) under acardinality constrained uncertainty set. The problem is reformulated as amixed-integer linear programming (MILP) and solved approximately by theiterative linear programming rounding algorithm. Numerical investigations showthat the minimum SR can be improved by 28.61% on average compared to fixedsmall cells.

Robust Deployment and Resource Allocation for Robotic Aerial Base Station Enabled OFDM Integrated Sensing and Communication