Reachability Analysis
Overview
Reachability analysis studies which states a system can reach over time, and whether it can reach a goal while avoiding unsafe states. Researchers use methods such as Hamilton–Jacobi equations, interval and zonotope set propagation, symbolic model checking, and reachability certificates to analyze dynamical systems, robots, games, and neural networks. Learning-based approaches approximate reachable sets or safety functions from data, sometimes adding probabilistic or formal guarantees, to support real-time planning and verification. A central challenge is scaling these methods to high-dimensional systems without making the results overly conservative or relying on inaccurate models.
Latest papers
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