Matti Vahs

Institute for Futures Studies, KTH Royal Institute of Technology

Papers

Total Citations

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About

Matti Vahs is a rising researcher in robotics and control theory, specializing in risk-aware control and safety-critical autonomy under uncertainty. His work addresses a fundamental challenge in real-world robotics: ensuring safe operation despite unmodeled dynamics, noisy sensors, and stochastic disturbances. Vahs’s major contributions lie in developing novel frameworks that integrate probabilistic state estimation—such as Kalman filters and non-Gaussian belief spaces—with control barrier functions and temporal logic planning. His most-cited paper, “Belief Control Barrier Functions for Risk-Aware Control” (2023, 11 citations), introduces a method to guarantee safety in belief space by explicitly accounting for estimation uncertainty. He has further extended this to spatio-temporal logic planning (2023, 4 citations) and non-Gaussian belief spaces (2024, 3 citations), broadening the applicability of risk-aware control. Vahs’s work on non-smooth control barrier functions for stochastic systems (2024, 2 citations) tackles complex safety specifications under environmental variations. With a growing citation footprint and a clear focus on bridging theory and practice, Vahs is establishing himself as a key voice in the next generation of safe autonomous systems—making his research essential reading for students and engineers tackling uncertainty in robotics.