7 papers
A Taylor Series Approach to Correct Localization Errors in Robotic Field Mapping using Gaussian Processes
Muzaffar Qureshi, Tochukwu Elijah Ogri, Kyle Volle +1
Gaussian Processes (GPs) are powerful non-parametric Bayesian models for regression of scalar fields, formulated under the assumption that measurement locations are perfectly known…
Safe Adaptive Feedback Control via Barrier States
Trivikram Satharasi, Tochukwu E. Ogri, Muzaffar Qureshi +2
This paper presents a safe feedback control framework for nonlinear control-affine systems with parametric uncertainty by leveraging adaptive dynamic programming (ADP) with barrier…
Safe Output-Feedback Adaptive Optimal Control of Affine Nonlinear Systems
Tochukwu E. Ogri, Muzaffar Qureshi, Zachary I. Bell +2
In this paper, we develop a safe control synthesis method that integrates state estimation and parameter estimation within an adaptive optimal control (AOC) and control barrier fun…
Improved Dwell-times for Switched Nonlinear Systems using Memory Regression Extension
Muzaffar Qureshi, Tochukwu Elijah Ogri, Humberto Ramos +3
This paper presents a switched systems approach for extending the dwell-time of an autonomous agent during GPS-denied operation by leveraging memory regressor extension (MRE) techn…
A Taylor Series Approach to Correction of Input Errors in Gaussian Process Regression
Muzaffar Qureshi, Tochukwu Elijah Ogri, Zachary I. Bell +2
Gaussian Processes (GPs) are widely recognized as powerful non-parametric models for regression and classification. Traditional GP frameworks predominantly operate under the assump…
A Switched Systems Approach to Image-Based Feature Tracking for Autonomous Satellite Inspection
Tochukwu Elijah Ogri, Muzaffar Qureshi, Zachary I. Bell +3
This paper presents an information-based guidance and control architecture for an autonomous deputy spacecraft tasked with inspecting a chief satellite in orbit. The primary object…