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Estimation of nonlinear dynamic models from data poses many challenges, including model instability and non-convexity of long-term simulation fidelity. Recently Lagrangian relaxation has been proposed as a method to approximate simulation…
We present an efficient transcription method for highly oscillatory optimal control problems. For these problems, the optimal state trajectory consists of fast oscillations that change slowly over the time horizon. Out of a large number of…
Energy efficiency is a crucial issue for maritime communications, due to the limitation of geographically available base station sites. Different from previous studies, we promote the energy efficiency by exploiting the specific…
Nonlinear optimal control problems for trajectory planning with obstacle avoidance present several challenges. While general-purpose optimizers and dynamic programming methods struggle when adopted separately, their combination enabled by a…
Data analysis and interpretation often relies on an approximation of an empirical dataset by some analytic functions or models. Actual implementations usually rely on a non-linear multi-dimensional optimization algorithm, typically…
The exploration of planetary surfaces is predominately unmanned, calling for a landing vehicle and an autonomous and/or teleoperated rover. Artificial intelligence and machine learning techniques can be leveraged for better mission…
Driven by increased complexity of dynamical systems, the solution of system of differential equations through numerical simulation in optimization problems has become computationally expensive. This paper provides a smart data driven…
Recent theoretical developments in astronomical aperture synthesis have revealed the existence of integer-ambiguity problems. Those problems, which appear in the self-calibration procedures of radio imaging, have been shown to be similar to…
In this paper, we investigate time-division based framework for integrated sensing, communication, and computing in integrated satellite-terrestrial networks. We consider a scenario, where Internet-of-Things devices on the ground operate…
Earth observation satellites generate large amounts of real-time data for monitoring and managing time-critical events such as disaster relief missions. This presents a major challenge for satellite-to-ground communications operating under…
In this work, we investigate resource allocation strategy for real time communication (RTC) over satellite networks with virtual network functions. Enhanced by inter-satellite links (ISLs), in-orbit computing and network virtualization…
This research explores the enhancement of lunar landing precision through an advanced structured light system, integrating machine learning, Iterative Learning Control (ILC) and Structured Illumination Microscopy (SIM) techniques. By…
We consider the problem of solving a large-scale system of linear equations in a distributed or federated manner by a taskmaster and a set of machines, each possessing a subset of the equations. We provide a comprehensive comparison of two…
This paper addresses the problem of distributed coordination control of spacecraft formation. It is assumed that the agents measure relative positions of each other with a non-zero, unknown constant sensor bias. The translational dynamics…
Upcoming large satellite constellations and the advent of tighter steerable beams will offer unprecedented flexibility. This new flexibility will require resource management strategies to be operated in high-dimensional and dynamic…
Spacecraft increasingly rely on heterogeneous computing resources spanning onboard flight computers, orbital data centers, ground station edge nodes, and terrestrial cloud infrastructure. Selecting where a workload should execute is a…
Agile satellites are the new generation of Earth observation satellites (EOSs) with stronger attitude maneuvering capability. Since optical remote sensing instruments equipped on satellites cannot see through the cloud, the cloud coverage…
This paper presents a novel robust trajectory optimization method for constrained nonlinear dynamical systems subject to unknown bounded disturbances. In particular, we seek optimal control policies that remain robustly feasible with…
Network slicing is a key technique in 5G and beyond for efficiently supporting diverse services. Many network slicing solutions rely on deep learning to manage complex and high-dimensional resource allocation problems. However, deep…
The upcoming landscape of Earth Observation missions will defined by networked heterogeneous nanosatellite constellations required to meet strict mission requirements, such as revisit times and spatial resolution. However, scheduling…