Related papers: Robust state and protection-level estimation withi…
This paper presents a novel Long Baseline (LBL) position and velocity navigation filter for underwater vehicles based directly on the sensor measurements. The solution departs from previous approaches as the range measurements are…
Adopting a joint approach towards state estimation and integrity monitoring results in unbiased integrity monitoring unlike traditional approaches. So far, a joint approach was used in Particle RAIM [l] for GNSS measurements only. In our…
With the advancement of transportation vehicles, the importance and utility of navigation systems providing positioning, navigation, and timing (PNT) information have been increasing. Global navigation satellite systems (GNSS) are widely…
A Markov decision process-based state switching is devised, implemented, and analyzed for proximity operations of various autonomous vehicles. The framework contains a pose estimator along with a multi-state guidance algorithm. The unified…
Reliable positioning in GNSS-challenged environments remains a critical challenge for navigation systems. Tightly coupled GNSS/IMU fusion improves robustness but remains vulnerable to non-Gaussian noise and outliers. We present a robust and…
This study introduces a novel methodology for controlling Quadrotor Unmanned Aerial Vehicles, focusing on Hierarchical Sliding Mode Control strategies and an Extended Kalman Filter. Initially, an EKF is proposed to enhance robustness in…
Control barrier functions-based quadratic programming (CBF-QP) is gaining popularity as an effective controller synthesis tool for safe control. However, the provable safety is established on an accurate dynamic model and access to all…
This work addresses the challenge of developing a localization system for an uncrewed ground vehicle (UGV) operating autonomously in unstructured outdoor Global Navigation Satellite System (GNSS)-denied environments. The goal is to enable…
The ensemble Kalman filter (EnKF) is a data assimilation technique that uses an ensemble of models, updated with data, to track the time evolution of a usually non-linear system. It does so by using an empirical approximation to the…
Autonomous robots relying on radio frequency (RF)-based localization such as global navigation satellite system (GNSS), ultra-wide band (UWB), and 5G integrated sensing and communication (ISAC) are vulnerable to spoofing and sensor…
We present an Extended Kalman Filter framework for system identification and control of a stochastic high-dimensional epidemic model. The scale and severity of the COVID-19 emergency have highlighted the need for accurate forecasts of the…
Autonomous unmanned aerial vehicle (UAV) inertial navigation exhibits an extreme dependency on the availability of global navigation satellite systems (GNSS) signals, without which it incurs in a slow but unavoidable position drift that may…
Location information is critical to a wide-variety of navigation and tracking applications. Today, GPS is the de-facto outdoor localization system but has been shown to be vulnerable to signal spoofing attacks. Inertial Navigation Systems…
Navigation in the cislunar domain presents significant challenges due to chaotic and unmodeled dynamics, as well as state-dependent sensor errors. This paper develops a robust estimation framework based on Linear Fractional Transformation…
In this paper, we present a fast and decentralized state estimation framework for the control of legged locomotion. The nonlinear estimation of the floating base states is decentralized to an orientation estimation via Extended Kalman…
Hybrid systems play a crucial role in modeling real-world applications where discrete and continuous dynamics interact, including autonomous vehicles, power systems, and traffic networks. Safety verification for these systems requires…
High-precision navigation and positioning systems are critical for applications in autonomous vehicles and mobile mapping, where robust and continuous localization is essential. To test and enhance the performance of algorithms, some…
We propose an ensemble score filter (EnSF) for solving high-dimensional nonlinear filtering problems with superior accuracy. A major drawback of existing filtering methods, e.g., particle filters or ensemble Kalman filters, is the low…
This paper investigates the state estimation problem for unknown linear systems subject to both process and measurement noise. Based on a prior input-output trajectory sampled at a higher frequency and a prior state trajectory sampled at a…
Multi-sensor fusion is an effective way to enhance the positioning performance of autonomous underwater vehicles (AUVs). However, underwater multi-sensor fusion faces challenges such as heterogeneous frequency and dynamic availability of…