Presents a successive convexification framework that enforces continuous-time STL specifications in trajectory optimization via GMSR robustness and prox-convex solving.
Signal temporal logic planning with time-varying robustness
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math.OC 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
The paper introduces diagnostic certificates that separately assess state-space coverage, lifted-feature nondegeneracy, and regression-spectrum quality for Koopman and EDMDc identification, with theoretical guarantees on the smallest singular value under a population spectral gap.
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Successive Convexification for Trajectory Optimization with Continuous-time Satisfaction of Signal Temporal Logic Specifications
Presents a successive convexification framework that enforces continuous-time STL specifications in trajectory optimization via GMSR robustness and prox-convex solving.
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Diagnostic Certificates of Data Quality and Regression Identifiability for Koopman Identification
The paper introduces diagnostic certificates that separately assess state-space coverage, lifted-feature nondegeneracy, and regression-spectrum quality for Koopman and EDMDc identification, with theoretical guarantees on the smallest singular value under a population spectral gap.