Convex Approach to Data-Driven Off-Road Navigation via Linear Transfer Operators

We consider the problem of optimal control design for navigation on off-road terrain. use a traversability measure to characterize difficulty The captures terrain properties essential navigation, such as elevation maps, roughness, slope, and texture. with presence or absence obstacles becomes particular case proposed measure. provide convex formulation by lifting density space using linear Perron-Frobenius (P-F) operator. leads an infinite-dimensional synthesis. construct finite-dimensional approximation optimization data. computational framework based data-driven Koopman This makes approach applicable cases where explicit system model is unavailable. Finally, we apply single integrator dynamics Dubin's car model.