Related papers: Precision Mars Entry Navigation with Atmospheric D…
Proton auroras are widely observed on the dayside of Mars, identified as a significant intensity enhancement in the hydrogen Lyman alpha (121.6 nm) emission between 110 - 150 km altitudes. Solar wind protons penetrating as energetic neutral…
After providing a brief historical overview on the synergies between artificial intelligence research, in the areas of evolutionary computations and machine learning, and the optimal design of interplanetary trajectories, we propose and…
A promising approach to improve climate-model simulations is to replace traditional subgrid parameterizations based on simplified physical models by machine learning algorithms that are data-driven. However, neural networks (NNs) often lead…
The Martian upper atmosphere is known to vary diurnally and seasonally due to changing amounts of solar radiation. However, in the upper thermosphere and exosphere, the neutrals are also subject to ion precipitation. This can increase the…
Accurate and high precision of the indoor positioning is as important as ensuring reliable navigation in outdoor environments. Using the state-of-the-art deep learning models provides better reliability and accuracy to navigate and monitor…
Remote sensing observations and Mars rover missions have recorded the presence of beaches, salt lakes, and wind erosion landforms in Martian sediments. All these observations indicate that Mars was hydrated in its early history. There used…
The performance of large-scale computing systems often critically depends on high-performance communication networks. Dynamically reconfigurable topologies, e.g., based on optical circuit switches, are emerging as an innovative new…
Since the beginning of robotic interplanetary exploration nearly six decades ago, successful atmospheric entry has been accomplished at Venus, Earth, Mars, Jupiter, and Titan. More entry probe missions are planned to Venus, Titan, and…
The Atmospheric Chemistry Suite (ACS) onboard the ExoMars Trace Gas Orbiter (TGO) monitors the Martian atmosphere through different spectral intervals in the infrared light. We present a retrieval algorithm tailored to the analysis of…
The essential of navigation, perception, and decision-making which are basic tasks for intelligent robots, is to estimate necessary system states. Among them, navigation is fundamental for other upper applications, providing precise…
Neural networks are a promising technique for parameterizing sub-grid-scale physics (e.g. moist atmospheric convection) in coarse-resolution climate models, but their lack of interpretability and reliability prevents widespread adoption.…
The midlatitude climate and weather are shaped by storms, yet the factors governing their predictability remain insufficiently understood. Here, we use a Convolutional Neural Network (CNN) to predict and quantify uncertainty in the…
While machine learning is traditionally a resource intensive task, embedded systems, autonomous navigation and the vision of the Internet-of-Things fuel the interest in resource efficient approaches. These approaches require a carefully…
Atmospheric retrievals (AR) characterize exoplanets by estimating atmospheric parameters from observed light spectra, typically by framing the task as a Bayesian inference problem. However, traditional approaches such as nested sampling are…
Key challenges in developing underwater acoustic localization methods are related to the combined effects of high reverberation in intricate environments. To address such challenges, recent studies have shown that with a properly designed…
Under a terraforming scenario, a reactivated hydrological cycle on Mars will result in upwards movement of water due to evaporation and precipitation. If Mars' embryonic fossilized catchments provide inadequate drainage, Mars' limited…
We consider the task of classifying trajectories of boat activities as a proxy for assessing maritime threats. Previous approaches have considered entropy-based metrics for clustering boat activity into three broad categories: random walk,…
Traversability estimation in rugged, unstructured environments remains a challenging problem in field robotics. Often, the need for precise, accurate traversability estimation is in direct opposition to the limited sensing and compute…
An algorithm based on Artificial Neural Networks is proposed in this paper to improve the accuracy of Inertial Navigation System (INS)/ Global Navigation Satellite System (GNSS) integrated navigation during the absence of GNSS signals. The…
Spacecraft operations are highly critical, demanding impeccable reliability and safety. Ensuring the optimal performance of a spacecraft requires the early detection and mitigation of anomalies, which could otherwise result in unit or…