4 papers
Particle-Based Conformal Prediction for Contact-Aware Uncertainty Calibration in Stratified Configuration Spaces
Luís Marques, Kristian Popov, Dmitry Berenson
Reliable uncertainty representation is essential for deploying autonomous systems that interact with their environment, as robots must reason about how uncertainty arising from bot…
Local Conformal Calibration of Dynamics Uncertainty from Semantic Images
Luís Marques, Dmitry Berenson
We introduce Observation-aware Conformal Uncertainty Local-Calibration (OCULAR), a conformal prediction-based algorithm that uses perception information to provide uncertainty quan…
Lies We Can Trust: Quantifying Action Uncertainty with Inaccurate Stochastic Dynamics through Conformalized Nonholonomic Lie groups
Luís Marques, Maani Ghaffari, Dmitry Berenson
We propose Conformal Lie-group Action Prediction Sets (CLAPS), a symmetry-aware conformal prediction-based algorithm that constructs, for a given action, a set guaranteed to contai…
Quantifying Aleatoric and Epistemic Dynamics Uncertainty via Local Conformal Calibration
Luís Marques, Dmitry Berenson
Whether learned, simulated, or analytical, approximations of a robot's dynamics can be inaccurate when encountering novel environments. Many approaches have been proposed to quanti…