2026
Data-Driven Anomaly Detection in Robots Using Matrix Chernoff Bounds
ICRA 2026poster
This work proposes a novel data-driven anomaly detection framework for robotic systems, grounded in statistical concentration inequalities. The method leverages the Matrix Chernoff Inequality to establish probabilistic bounds on the eigenvalues of cumulative error covariance matrices computed over a…