Search Results (1,109)

This paper studies the compressible spherically symmetric Euler equations with a vacuum free boundary, a fundamental model for astrophysical gas dynamics. We rigorously resolve an open problem by proving that nontrivial homogeneous linear velocity solutions exist if, and only if, the adiabatic exponent $\gamma =4/3$, the critical value for monatomic gases and radiative stellar atmospheres. Using qualitative analysis of the reduced planar dynamical system, we characterize the flow’s global existence and finite-time blow-up behavior, establish a sharp existence threshold, and derive an explicit upper bound for the blow-up time. Quantitative energy estimates via Bernoulli’s head verify the physical consistency of solutions in both regimes. Our results complete the classification of self-similar solutions in this class, laying a rigorous theoretical foundation for planetary atmospheric gas flows and providing a practical criterion for predicting blow-up. Full article

As human space missions become longer and more autonomous, robots are expected to assume broader responsibilities in inspection, maintenance, logistics, scientific support, and crew assistance. Among available robot forms, humanoid robotic astronauts are especially relevant because their anthropomorphic embodiment is compatible with human-centered habitats, tools, interfaces, and procedures. Their deployment in orbital and planetary environments, however, introduces challenges that differ from those of terrestrial humanoids, including floating-base dynamics, intermittent contact, whole-body coordination, constrained perception, and delayed supervision. This review contributes a mission-oriented and astronaut-centered synthesis of humanoid robotic astronauts, distinguishing itself from platform-by-platform or morphology-only surveys. It treats these systems as mission-compatible embodied agents whose feasibility depends on the coupling among mission context, morphology, contact behavior, perception, autonomy, and validation evidence. The primary goals are threefold: to classify representative platforms according to mission context, to synthesize the core technical foundations required for mission-compatible operation, and to identify cross-cutting deployment bottlenecks and benchmarking priorities for future development. Representative systems are organized into intravehicular assistance, extravehicular operations and on-orbit servicing, and surface exploration or transitional scenarios, showing how mission demands shape embodiment, mobility, manipulation, autonomy, and validation strategies. This review further summarizes recent progress in microgravity dynamics and contact mechanics, multimodal perception and scene understanding, whole-body motion planning and control, teleoperation and supervised autonomy, and evaluation and benchmarking methods. The analysis indicates that humanoid robotic astronauts are not simple extensions of terrestrial humanoids but astronaut-oriented embodied systems for mission-constrained environments. Three priorities are identified for future development: contact-rich whole-body intelligence under support transitions, delay-tolerant supervised autonomy with explicit authority handoff, and systematic benchmarking pipelines that connect simulation, ground analogs, short-duration microgravity tests, human-in-the-loop trials, and mission-context demonstrations. Full article

In response to the demands for planetary material detection, in this study, we propose an optical system for a compact remote Raman–LIBS (CRBS, Laser-Induced Breakdown Spectroscopy) combined spectrometer based on liquid lens focusing. This system adopts a design approach incorporating liquid lens focusing, a shared pulsed excitation source, and a common optical path for both transmission and reception. Compared to existing international combined Raman–LIBS spectrometer systems, the proposed optical system is more compact and achieves integrated Raman and LIBS detection capabilities, thereby facilitating system miniaturization and enhancing detection efficiency. This system represents a promising approach for compact, robust remote surface analysis instruments for terrestrial and planetary science. This study provides a theoretical foundation for achieving stable in-orbit detection in lunar material exploration and other long-distance signal detection missions. Full article

Celestial bodies in the solar system have long been of particular interest in space science. Some questions, e.g., those concerning the origin of life, require on-site landing and exploration. Due to signal delay, some degree of autonomy provided by artificial intelligence (AI) is needed. Motivated by planetary exploration missions, the German Research Center for Artificial Intelligence (DFKI) has developed methods for (semi-)autonomous control of vehicles and robots on extraterrestrial bodies. To validate the software, we conduct extensive field tests in terrestrial analog environments. Field tests can be seen as an intermediate step between development and laboratory testing and real-world deployment in an extraterrestrial environment. This paper describes the challenges of testing AI and robotic systems in analog environments, with a focus on the additional dependencies that arise during the preparation and execution of such field tests. The robots and software tested in these field tests are based on more than a decade of development across various projects, covering a wide range of AI systems and applications, including geometric planning, probabilistic perception, deep learning, and robot construction for open challenges in planetary exploration. Full article

When the global energy transition is analyzed through economic lenses, the constraints imposed by the laws of thermodynamics are often overlooked. This study addresses the Latecomer’s Dilemma—the predicament of semi-peripheral nations compelled to decarbonize without the capital stock accumulated following the example of the countries of the Global North during their more than two hundred years of industrial development associated with the saturation of the atmosphere with carbon dioxide. A novel phase space model of the Anthropocene is constructed, synthesizing the political concept of ecological debt with the biophysical reality of entropy debt. The application of the laws of systems ecology and non-equilibrium thermodynamics enables the mapping of national development trajectories against the saturated “atmospheric bathtub”. The analysis identifies a critical Injustice Gap—a region of phase space physically foreclosed by historical emissions. Moreover, it has been demonstrated that a circular economy powered by low-density renewables functions as an entropy trap, converting material debt into radiative debt without achieving a closed loop. Consequently, the Polish correction vector is proposed as a stabilization mechanism. This study’s findings indicate that addressing the emerging phenomenon of adaptation apartheid necessitates the implementation of a high-density energy flux, namely Generation IV nuclear reactors, which would be funded by a retroactive ETS3 mechanism. This approach fulfills the thermodynamic condition for material closure, thereby substantiating the notion that energy justice constitutes a physical necessity for planetary stability. This study quantifies the historical radiative debt of a single early-industrialized hub (Manchester) at approximately 142.8 billion EUR. The novelty lies in the synthesis of biophysical laws and the Latecomer’s Dilemma through the proposed ETS3 mechanism. Full article

Accelerating environmental degradation and the continued overshoot of planetary boundaries highlight the urgent need for scientifically grounded sustainability assessments that operate across scales. While the planetary boundaries framework provides a global reference for safe environmental limits, its translation to regional and local contexts remains a methodological and practical challenge. In response, this study presents a novel scalable framework for conducting regionally explicit assessments of absolute environmental sustainability, grounded in the planetary boundaries framework. The central objective is to enable scientifically robust and globally comparable evaluations that remain sensitive to local environmental and socioeconomic conditions. The method integrates historical environmental datasets, and satellite-based Earth observation, to assess environmental impacts at the regional scale. A structured three-step process is introduced: (1) regional thresholds are derived from historical reference conditions; (2) thresholds are validated using Earth observation; and (3) environmental impacts are quantified against the validated thresholds to detect transgressions. The framework was tested in the urban core of Kiruna, northern Sweden, across five planetary boundary indicators. The results reveal substantial boundary transgressions, most notably for genetic diversity, which reaches 269 extinctions per million species-years, and for land system change, where the regional threshold is fully exceeded. These findings illustrate both the analytical value and the methodological challenges of applying planetary boundaries at fine spatial scales. Kiruna, northern Sweden, was selected as a case study due to its role as a European mining center, its location within Sámi territories, and the overlap between resource extraction and settlement. The case study illustrates the difficulty of applying planetary boundaries at fine spatial scales. This highlights the need for careful interpretation and improved calibration when downscaling global thresholds to local conditions. Ultimately, the framework reveals the potential and limitations of regionalizing planetary boundaries, highlighting the importance of methodological transparency and contextual nuance in sustainability assessment. Full article

This paper introduces a new single-objective formulation of the mixed-integer Cassini2 interplanetary trajectory problem (Cassini2-MINLP), extending the GTOPX benchmark library. The formulation introduces four additional decision variables that determine the sequence of intermediate planetary flybys, expanding the set of feasible trajectories and increasing the dimensionality, flexibility, and structural complexity of the trajectory design problem. The resulting search space is 26-dimensional, consisting of 22 continuous trajectory variables and four variables encoding the discrete flyby sequence. The mission scenario assumes a fixed departure from Earth and arrival at Saturn, while the intermediate flyby planets are selected from the set of major Solar System planets. The encounter sequence is modeled using discrete variables derived from a relaxed continuous encoding through rounding and bounding operations, resulting in a mixed-integer nonlinear programming (MINLP) problem. The objective is to minimize the total $\Delta V$, representing propellant consumption and overall energetic efficiency. To evaluate algorithmic performance on this challenging benchmark, eight well-established and recent optimization algorithms from three methodological families (ACO, DE, and CMA-ES) are evaluated under a consistent experimental setup with fixed random seeds to ensure reproducibility. Statistical analyses based on the 30 independent runs using the Friedman test confirm highly significant differences among the algorithms, with the DISHr algorithm achieving the best average rank at value 1.567 and statistically outperforming several other competing methods according to the Nemenyi post-hoc test. The results demonstrate that the Cassini2-MINLP formulation provides a challenging and practically relevant benchmark for trajectory optimization and establishes a foundation for future research on multi-objective formulations and advanced optimization strategies for complex interplanetary missions. Full article

Planetary exploration has increasingly relied on mobile robots known as rovers to support space development. Among various locomotion systems, legged mechanisms have attracted attention as a promising approach for achieving high mobility on rough terrain. However, the surfaces of extraterrestrial bodies such as the Moon and Mars are covered with loose regolith that easily deforms under external forces. As a result, legged rovers tend to disturb the ground surface and experience slippage due to leg-induced loading. To address this issue, a previous study proposed a novel walking method in which the rover’s leg applies vibration to the soil before stepping to compact it. Experiments confirmed that this vibration increases the soil’s bearing capacity, defined as its resistance to vertical loading. This increase is attributed to improvements in soil density and particle interconnectivity, which enhance soil shear strength. In this study, the relationship between the bearing capacity of vibration-compacted soil and its shear strength is investigated through experiments. The results reveal a clear correlation between these parameters, indicating that the bearing capacity of vibration-compacted soil can be estimated from shear strength measurements. Full article

A software autonomy framework provides a vital solution to the challenges posed by growing congestion in Earth’s orbits and the increasing complexity of planetary exploration. For satellite constellations, IOS & ISAM missions, autonomy minimizes dependence on ground control by enabling real-time decision-making for spacecraft collision avoidance, client capture, robotic servicing operations, resource optimization, and resilience against cyber threats in a crowded and geopolitically sensitive space environment. Similarly, autonomous frameworks allow rovers to operate efficiently on distant planets, where communication delays make manual control impractical. By integrating adaptive navigation, fault management, and cooperative behaviors, these systems enhance mission success, reduce operational costs, and ensure rapid responses to dynamic conditions, both in orbit and on planetary surfaces. This paper presents the ERGO Autonomy SW Framework as a mature solution to deal with these space challenges. Full article

With the increasing number of space research projects, systems that can be flexibly adapted to the respective orbital and planetary mission requirements and modified retrospectively as needed are becoming increasingly interesting. One application for this is modular robot systems that can be combined or exchanged as needed via electromechanical interfaces without having to replace the entire system. Due to current activities in the EU, such as the Space USB project, the trend is going towards the development of a universal standard interface (USI) that, among other things, has functions for mechanical coupling and the transmission of electrical energy and data. To be able to couple different USIs with each other, one possible solution will be the use of an adapter. This paper presents such an adapter, as well as tests that have been carried out and the lessons learned from them. Full article

Artificial intelligence applications in mental health diagnosis face persistent challenges related to interpretability, trust, and the integrity of results. This study presents a trust-aware explainable deep learning framework that combines systematic benchmarking, SHAP-based interpretability, and permissioned blockchain verification to achieve secure mental health classification. The Depression & Mental Health Classification Dataset was used, which contains 1999 records, 21 features, and 12 classes. Data preprocessing included categorical encoding and Z-score normalization for continuous variables. To ensure robust evaluation, a stratified train–test split was applied, and class imbalance was addressed using the Synthetic Minority Over-sampling Technique (SMOTE). Eight machine learning and deep learning models were assessed under identical preprocessing and validation settings. In addition, two models were proposed: Feature Attention XGBoost (FA-XGBoost) and Feature Attention Feedforward Neural Network (FA-FNN). The FA-FNN model achieved the best performance, attaining an accuracy of 96.00%, precision of 98.31%, recall of 97.31%, and F1-score of 98.04%. To address deep learning’s black-box limitation, SHapley Additive ExPlanations (SHAPs) were used to provide both global feature importance and instance-level explanations, enabling transparent identification of the most influential mental health markers. Beyond interpretability, a permissioned blockchain layer was added to provide tamper-proof logging and traceable verification of AI results. The framework securely stores cryptographic hashes of model versions, prediction results, and generated SHAP artifacts, including visualization images, without exposing sensitive medical data. By integrating explainable decision-making, high-performance classification, and blockchain-based trust enforcement, the proposed framework creates a transparent and secure pipeline suitable for real-world mental healthcare systems. Controlled experiments on a permissioned Ethereum-InterPlanetary File System (IPFS) network demonstrated predictable latency, stable throughput (≈28–30 transactions/s), and lower operational costs, proving the framework’s suitability for enterprise and healthcare deployments. Full article

Addressing the challenges of privacy leakage, fragmented data silos, and high computational overhead in traditional ciphertext-policy attribute-based encryption (CP-ABE) for medical data sharing, this paper proposes an improved CP-ABE framework with outsourced decryption, integrated with consortium blockchain and the InterPlanetary File System (IPFS). The framework introduces a medical-scenario-adapted CP-ABE architecture based on a lightweight FAME design, optimizing attribute key generation and transformation key design to accommodate resource-constrained medical terminals. A hybrid encryption system is employed, combining symmetric encryption for high-efficiency processing of large medical data and CP-ABE for fine-grained access control of symmetric keys. To reduce user computational burden, a proxy-assisted secure decryption architecture is implemented, where the proxy server handles most decryption tasks while ensuring resistance to malicious proxy behavior. Furthermore, the framework provides rigorous formal security verification, achieving IND-CPA security and resilience against collusion and malicious proxy attacks. Comprehensive performance evaluations demonstrate significant improvements in key generation, encryption, and decryption efficiency, offering a better balance between security and efficiency for practical medical data sharing applications. Full article

The Research and Observation in Medium Earth Orbit (ROMEO) mission, developed at the University of Stuttgart‘s Institute of Space Systems, seeks to demonstrate a cost-effective exploitation of the medium Earth orbit (MEO) for sustainable access to space. It uses a green propulsion system with water as propellant to reach up to 2500 km altitude starting from a 450 km sun-synchronous orbit (SSO). This paper presents the design and intended use of the ROMEO satellite as well as its two in-house developed camera systems, the public relations (PR) and the near-infrared (NIR) camera system. The PR camera system features two silicon sensors with a Bayer color pattern in a compact, lightweight package and in a cold redundant setup to reduce the impact of radiation-related degradation. Their wide field of view (128 × 96°) allows imaging of the complete visible Earth in the mission‘s final orbit and supports calibration of the Earthshine telescope, which is the primary payload. The NIR camera system uses a commercial InGaAs sensor with a high quantum efficiency up to 1700 nm, coupled to a 100 mm focal length optics assembly that yields a ground sampling distance of 45 m in the initial orbit. Its scientific objectives include monitoring gas flares and wildfires, which are relevant to climate change research, and demonstrating an exoplanet transit detection—an unprecedented capability for a small satellite using a commercial off-the-shelf InGaAs sensor in the NIR spectrum. This paper demonstrates that ROMEO’s compact, low-mass camera systems meet mission constraints while enabling a broad spectrum of scientific and outreach activities. Full article

Climate change has emerged as a defining global crisis, with the frequency and intensity of climate-induced disasters rising sharply and imposing disproportionate costs on developing economies and small island states. This article examines the role of climate-resilient infrastructure as a central pillar of climate-smart growth, integrating mitigation, adaptation, and long-term development objectives. It situates climate-resilient infrastructure within a planetary health setting, emphasizing the interdependence between human well-being, ecological systems, and infrastructure resilience. Climate-resilient infrastructure, not merely seen as an engineering solution but as a public good that generates significant positive externalities, reduces systemic macroeconomic risk and delivers welfare gains that exceed private financial returns. It discusses the cross-country heterogeneities in resilience outcomes, driven by differences in geographic exposure, economic capacity, institutional quality, and political economy constraints. Building on this, the study advances a welfare-based approach to infrastructure prioritization that incorporates service disruptions, distributional impacts, and fiscal risk, rather than asset values alone. It further outlines policy and financing strategies to bridge the gap between social and private returns, including public investment, concessional finance, blended instruments, and nature-based solutions. By embedding infrastructure within a planetary health lens, the paper argues that resilient systems are critical not only for safeguarding lives and livelihoods, but also for sustaining ecological stability, reducing health risks, and enabling inclusive, sustainable, and climate-smart economic growth. Full article

Existing methods for selecting the number of teeth in complex planetary gear systems are often methodologically demanding. They do not always ensure all conditions required for proper operation and assembly. This paper presents an analytical methodology for determining gear tooth numbers. The method is demonstrated on a Ravigneaux planetary gear set with seven kinematic links and two degrees of freedom. It ensures the simultaneous satisfaction of all meshing and assembly conditions. Starting from the known transmission ratios, the number of teeth of one central gear, and the selected angular displacement of the outer planet gear, analytical relationships are derived. These allow the determination of the tooth numbers of all remaining gear elements. The procedure is implemented in Python 3.13. This enables a systematic evaluation of predefined input ranges and an automatic verification of geometric constraints, including interference and undercutting conditions. The proposed method yields six feasible configurations. Compared with the Borg-Warner M85 automatic transmission, deviations in individual gear ratios reach up to 10%. Significantly lower tooth numbers are achieved for several gears. These results suggest that the proposed methodology can achieve comparable kinematic performance while offering more compact gear designs and a potential weight reduction. The developed model also provides a basis for extension to more complex configurations and integration with optimisation and dynamic criteria in planetary gear synthesis. Full article