no code implementations • 20 Sep 2023 • Domenico Parente, Nastaran Darabi, Alex C. Stutts, Theja Tulabandhula, Amit Ranjan Trivedi
This paper introduces a lightweight uncertainty estimator capable of predicting multimodal (disjoint) uncertainty bounds by integrating conformal prediction with a deep-learning regressor.
no code implementations • 18 Sep 2023 • Alex C. Stutts, Danilo Erricolo, Sathya Ravi, Theja Tulabandhula, Amit Ranjan Trivedi
In the expanding landscape of AI-enabled robotics, robust quantification of predictive uncertainties is of great importance.
no code implementations • 3 Mar 2023 • Alex C. Stutts, Danilo Erricolo, Theja Tulabandhula, Amit Ranjan Trivedi
Data-driven visual odometry (VO) is a critical subroutine for autonomous edge robotics, and recent progress in the field has produced highly accurate point predictions in complex environments.
no code implementations • 27 Oct 2022 • Priyesh Shukla, Sureshkumar S., Alex C. Stutts, Sathya Ravi, Theja Tulabandhula, Amit R. Trivedi
We present a novel monocular localization framework by jointly training deep learning-based depth prediction and Bayesian filtering-based pose reasoning.