2026· American Journal of Student Research· pp. 269-282· 0 citations
TL;DR
The proposed concept adds engineering soundness by mapping Mars hazards to decision-support functions, defining human-authority requirements, identifying safety and planetary-protection guardrails, and laying out a staged validation pathway from concept review to tabletop exercises, analog missions, digital twins, and eventually certified operational systems.
Abstract
Future human missions to Mars will place astronauts in a world that is scientifically rich but
physically unforgiving. The Martian surface has a thin atmosphere, extreme temperature swings, dust
activity, radiation exposure, delayed communication with Earth, limited resupply, and full dependence
on engineered life-support systems. These conditions make Mars exploration a safety-critical, distributed
teamwork problem rather than a simple task-planning problem. This article develops a conceptual
framework for human-artificial intelligence (AI) teamwork in Mars surface exploration. No detailed
mathematical model is proposed, no AI system is trained, no operational performance is claimed, and
no crewed test has been performed. Instead, the contribution is a research-grounded engineering concept
organized around Figure 1, in which mission readiness, in-mission support, human review, spacecraft
and habitat architecture, and data-to-value feedback form a closed safety loop. The framework argues
that AI should not replace astronauts or mission-control teams; rather, AI should act as a safety translator
that turns environmental data, system telemetry, robot reports, and science priorities into explainable
options for human approval. The proposed concept adds engineering soundness by mapping Mars
hazards to decision-support functions, defining human-authority requirements, identifying safety
and planetary-protection guardrails, and laying out a staged validation pathway from concept review
to tabletop exercises, analog missions, digital twins, and eventually certified operational systems.
The central message is that the smartest path to Mars is neither full automation nor unaided human
courage, but disciplined human-AI-robot teamwork that helps explorers remain safe, aware, ethical, and
scientifically productive.
Modern power grids require safer and more reliable field operations, yet conventional robots often face limitations in unstructured environments because of rigid pre-programming and weak perception–action coupling. This review examines Embodied Intelligence (EI) as an emerging direction for enhancing power-system field operations. We first evaluate the environmental adaptability of morphological carriers, including quadrupeds, humanoids, and unmanned aerial vehicles, and then define the perception–cognition–execution closed-loop architecture used in this review. Three application domains are then examined. Intelligent inspection focuses on active perception and potential open-vocabulary object detection. Live-line maintenance emphasizes Sim-to-Real methods and shared autonomy, while disaster-response applications involve heterogeneous air–ground robotic coordination. The review also discusses the potential for EI to reduce human exposure to hazardous tasks and influence labor structures, while a regional text-based proxy illustrates differences in policy attention to digital infrastructure. Finally, we analyze major constraints, including hardware endurance under extreme climates, edge-computing latency, foundation-model uncertainty and hallucination, cybersecurity, and safety certification. Overall, EI should not be interpreted as a mature replacement for current utility practice; it is a developing technological direction whose safe deployment will require field validation, standardized evaluation, cybersecurity assurance, and continued human supervisory authority.
Yuxin Wen, Peixiao Fan, Zhiyu Mao et al.· Applied Informatics· 0 citations
Human exploration missions beyond low earth orbit, such as NASA’s Artemis Program, present significant challenges to spacecraft system design and supportability. A particularly challenging area is the Environmental Control and Life Support System (ECLSS) that maintains a habitable and life-sustaining environment for crewmembers. NASA is utilizing the experience gained from its current and prior spaceflight programs to mature life support technologies for exploration missions to deep space. The intent is to establish a portfolio of life support system capabilities with proven performance and reliability to enable human exploration missions and reduce risk to success of those missions. As a fully operational human-occupied platform in microgravity, the International Space Station (ISS) presents a unique opportunity to act as a testbed for exploration-class ECLSS, such that these systems may be tested, proven, and refined for eventual deployment on deep space human exploration missions. This paper will provide an updated status on the testbed development including hardware and ISS vehicle integration progress to date as well as future plans for efforts to design, select, build, test and fly Exploration ECLSS on the ISS. This paper will provide an update on ISS advancements for the past two years.
Christopher A. Brown, K. Toon, David M. Hornyak et al.· 55th International Conferenc...· 0 citations
The results demonstrate the feasibility of transforming centralized ground support into a resilient, autonomous partner capable of safeguarding crew during high-latency planetary exploration.
Kaisheng Li, R. Whittle· 55th International Conferenc...· 0 citations
GAIN-AI (Guided Assistant for Intelligent Navigation), a context-aware AI assistant and minimal heads-up interface for procedural guidance in simulated lunar EVA, is presented.
Future Lunar and Martian exploration missions heavily rely on the ability to deploy advanced robotic infrastructures capable of operating fully autonomously in extreme planetary environments. Building such high-value, autonomous scientific and logistical capabilities is essential for supporting planetary science, mapping in-situ resources, and preparing long-duration human and robotic missions. The present study is part of CNES Spaceship France project's roadmap developing innovative solutions for future Habitat for Moon and Mars exploration, and focuses on assessing the architecture of an autonomous lunar surface laboratory deployed on ESA’s Argonaut EL3 lander. The laboratory is supported by a dedicated rover responsible for subsurface geological sampling and soil excavation. The mission is built around four core objectives: performing in-situ geological analysis of rover-delivered samples, conducting small-scale in-situ manufacturing demonstrations, establishing a geological repository that preserves collected samples and enables their retrieval and return on future missions, and providing a charging hub for the rover. A comprehensive suite of scientific and technology-demonstration instruments has been identified to support the mission objectives. Environmental drivers were incorporated into all functional and architectural trade-offs. The outcome is a comprehensive preliminary design of an autonomous lunar surface laboratory, detailing its internal architecture, subsystem interfaces, workflow layout, and accommodation of scientific and support functions. This work demonstrates the technical feasibility of the concept and outlines the critical technologies to reach operational readiness. Such a robotic infrastructure represents a strategic element of space exploration, providing a gap-filling platform that significantly enhances autonomous surface operations capabilities on planetary environments, and enables long-duration, more complex missions.
Antoine Marin, G. Collange, Grégory Navarro· 55th International Conferenc...· 0 citations
Abstract. The increasing number of space exploration missions presents a novel challenge with regards to planning and operations. Current architectures are composed of distinct teams and models performing separate tasks like navigation, planning, and science, which can lead to inefficiencies and delays. This work proposes a Digital Twin (DT) architecture which supports end-to-end mission design, operations, and scientific analysis. The proposed DT combines models of the spacecraft, its scientific payloads, and the target body, linked through a data processing layer that enables continuous monitoring, simulation, and decision support. A case study of a spacecraft exploring an asteroid and interacting with its surface through a lander and sampling arm is presented. This example specifically shows the importance of reduced order models (ROMs) to efficiently predict and interpret surface interactions. This approach highlights the potential of integrated DT architectures to enhance coordination, adaptability, and scientific return in future deep space missions.
Iosto Fodde· Materials Research Proceedin...· 0 citations
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