Artificial Intelligence in Space Exploration

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), 2020

An overarching principle accepted by space-faring nations and industry alike is to maintain freedom of operations in a safe and secure environment, commensurate with national and commercial interests. Deterrence concepts and escalation control play key roles in realizing this principle in the increasingly congested, competitive and contested space environment. AI and autonomous machine learning are being pursued as critical enablers in commercial and military programs for space traffic management, routine space operations, space domain awareness (SDA), and space control. AI systems hold the potential to strengthen deterrence by improving both the speed and ability to assess threats and inform decision makers in times of crisis. However, issues that have arisen in terrestrial AI applications will be also present in these applications, with implications for space deterrence and escalation scenarios. Key among these are performance, explainability, and vulnerability. To date there are few if any international standards or regulations to guide best practices for choosing AI methods for space operations and developing a shared understanding of the risks and benefits to strategic stability. This paper explores trade-offs between explainability, performance, and vulnerability in AI methods applied to space control and SDA scenarios, and illustrates how choices on these trade-offs may affect deterrence signaling and escalation control in space.

The ambitious short-term and long-term goals set down by the various national space agencies call for radical advances in several of the main space engineering areas, the design of intelligent space agents certainly being one of them. In recent years, this has led to an increasing interest in artificial intelligence by the entire aerospace community. However, in the current state of the art, several open issues and showstoppers can be identified. In this chapter, we review applications of artificial intelligence in the field of space engineering and space technology and identify open research questions and challenges. In particular, the following topics are identified and discussed: distributed artificial intelligence, enhanced situation self-awareness, and decision support for spacecraft system design.

2020

An overarching principle accepted by space-faring nations and industry alike is to maintain freedom of operations in a safe and secure environment, commensurate with national and commercial interests. Deterrence concepts and escalation control play key roles in realizing this principle in the increasingly congested, competitive and contested space environment. AI and autonomous machine learning are being pursued as critical enablers in commercial and military programs for space traffic management, routine space operations, space domain awareness (SDA), and space control. AI systems hold the potential to strengthen deterrence by improving both the speed and ability to assess threats and inform decision makers in times of crisis. However, issues that have arisen in terrestrial AI applications will be also present in these applications, with implications for space deterrence and escalation scenarios. Key among these are performance, explainability, and vulnerability. To date there are ...

BULLETIN OF "CAROL I" NATIONAL DEFENCE UNIVERSITY

This article critically assesses the transformative role of Artificial Intelligence (AI) in military operations, focusing on terrestrial warfare and outer space security. It offers four main points of discussion: 1) An evaluation of AI applications in terrestrial warfare, using real-world technologies such as Project Maven and BAE Systems’ Taranis; 2) an examination of AI’s contributions and risks in the field of cybersecurity; 3) an in-depth look at AI’s growing influence in space security, including technical aspects of systems like the U.S. Space-Based Infrared and the European Data Relay System; 4) an analysis of the ethical and policy challenges associated with AI deployment, informed by the author’s viewpoints on the necessity of international regulation. Drawing from various case studies and expert consultations, the article highlights AI’s capabilities in enhancing decision-making and operational efficiency while discussing the ethical and technical complexities it introduce...

ACM Transactions on Intelligent Systems and Technology, 2012

Telematics and Informatics, 1988

In response to a number of high-level strategy studies in the early 1980s, Expert Systems and Artificial Intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date and, hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant.

arXiv (Cornell University), 2022

& Proceedings 저널· 프로시딩즈| 기술 …

This paper discusses research and development of applications of artificial intelligence technology at JPL which solve mission-specific challenges in the areas of spacecraft autonomy and enhanced science return. These applications are a component of JPL's long term program to develop autonomy technology which enables the exploration of uncertain, changing environments and which supports creation of a vigilant, sustained presence in space. A broad array of artificial intelligence applications are underway at JPL and a selection of these will be surveyed with particular focus in the areas of self-commanding spacecraft, distributed autonomous systems, and closed-loop science autonomy. The paper will tie these areas together and conclude by highlighting the key challenges for artificial intelligence and autonomy technology which arise in future exploration missions to the solar system.

Ai Magazine, 1997

Machine Learning, 2011

We introduce the challenge of using machine learning effectively in space applications and motivate the domain for future researchers. Machine learning can be used to enable greater autonomy to improve the duration, reliability, cost-effectiveness, and science return of space missions. In addition to the challenges provided by the nature of space itself, the requirements of a space mission severely limit

iiis.org

The history of artificial intelligence control systems for use in space is discussed in this paper. The two fields started separately in the 1950s and first merged in the 1970s due to control requirements for a Jet Propulsion Laboratory project. While spacecraft have a special need for AI systems due to communications delays and other factors, much of AI control system development is conducted for earth-based applications. To mitigate risk factors, space-bound AI systems are also tested extensively via simulations. As a result, virtually all AI space control systems get their start on the ground. Additionally, ground support systems are required to facilitate communication with and command of AI controlled and other space craft. Numerous successful missions incorporating or controlled by AI technology have been launched. Further, many more are planned. Examples of ground, space-flown and future AI control missions are all discussed herein. While, spacecraft AI was born out of necessity (due to communication delays and such), it is now becoming desirable for other reasons such as cost savings and mission enhancement.

A recurring topic in interstellar exploration and the search for extraterrestrial intelligence (SETI) is the role of artificial intelligence. More precisely, these are programs or devices that are capable of performing cognitive tasks that have been previously associated with humans such as image recognition, reasoning, decision-making etc. Such systems are likely to play an important role in future deep space missions, notably interstellar exploration, where the spacecraft needs to act autonomously. This article explores the drivers for an interstellar mission with a computation-heavy payload and provides an outline of a spacecraft and mission architecture that supports such a payload. Based on existing technologies and extrapolations of current trends, it is shown that AI spacecraft development and operation will be constrained and driven by three aspects: power requirements for the payload, power generation capabilities, and heat rejection capabilities. A likely mission architecture for such a probe is to get into an orbit close to the star in order to generate maximum power for computational activities, and then to prepare for further exploration activities. Given current levels of increase in computational power, such a payload with a similar computational power as the human brain would have a mass of hundreds to dozens of tons in a 2050 – 2060 timeframe.

Engineering International, 2020

When writing about the history of the internet, it is important to note that aerospace was among the significant pioneers in computer networking computer network for private was used in first airline reservation system “SABRE” in 1960 for American airlines. While sage was the first computer system in the world, its deficiencies led to the development of ARPANET. These systems formed the foundations for the internet and the development of other computer programs in aerospace, any deficiency led to the invention of a new program, giving birth to programming, CAD, and CAM that brought about simulations. Aerospace computing has evolved over the years and is now carrying the whole weight of the aerospace industry. Before the launch of any space vehicle or satellite, simulation has become a necessary step, checking for weaknesses for corrections to be done on the ground. Besides, computer simulation has been essential in training, facilitating the training of pilots worldwide. This articl...

1993

The purpose of this report is to describe the applications of Artificial Intelligence (AI) to the European Space program that are being developed or have been developed. This report describes the results of a study sponsored by the Artificial Intelligence Research and Development program of NASA's Office of Advanced Concepts and Technology (OACT). The report is divided into two sections. The first consists of site reports, which are descriptions of the AI applications we saw at each place we visited. The second section consists of two summaries which synthesize the informa- tion in the site reports by organizing this information in two different ways. The first organizes the material in terms of the type of application, e.g., data analysis, planning and scheduling, and proce- dure management. The second organizes the material in terms of the component technologies of Artificial Intelligence which the applications used, e.g., knowledge based systems, model based reasoning, procedural reasoning, etc. ...

Acta Astronautica, 1992

This paper presents an artificial intelligence approach to integrated human-machine intelligence in space systems. It discusses the motivations for Intelligent Assistant Systems in both nominal and abnormal situations. The problem of constructing procedures is shown to be a very critical issue. In particular, keeping procedural experience in both design and operation is critical. We suggest what artificial intelligence can offer in this direction. Some crucial problems induced by this approach are discussed in detail. Finally, we analyze the various roles that would be shared by both astronauts, ground operators, and the intelligent assistant system.