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Abstract: "This paper describes the Remote Agent flight experiment for spacecraft commanding and control. In the Remote Agent approach, the operational rules and constraints are encoded in the flight software. The software may be considered to be an autonomous 'remote agent' of the spacecraft operators in the sense that the operators rely on the agent to achieve particular goals. The experiment will be executed during the flight of NASA's Deep Space One technology validation mission. During the experiment, the spacecraft will not be given the usual detailed sequence of commands to execute. Instead, the spacecraft will be given a list of goals to achieve during the experiment. In flight, the Remote Agent flight software will generate a plan to accomplish the goals and then execute the plan in a robust manner while keeping track of how well the plan is being accomplished. During plan execution, the Remote Agent stays on the lookout for any hardware faults that might require recovery actions or replanning. In addition to describing the design of the remote agent, this paper discusses technology-insertion challenges and the approach used in the Remote Agent approach to address these challenges. The experiment integrates several spacecraft autonomy technologies developed at NASA Ames and the Jet Propulsion Laboratory: on-board planning, a robust multi-threaded executive, and model-based failure diagnosis and recovery."
High-Reliability Autonomous Management Systems for Spacecraft updates on research on three levels of self-management, including: 1) Autonomous health management of spacecraft that covers how spacecraft can monitor their own state and autonomously detect, isolate and recover from faults; 2) Autonomous mission management of spacecraft where the spacecraft can directly receive the mission, formulate a reasonable plan according to the current state and working environment of the spacecraft, and convert the mission into a specific sequence of instructions; 3) Spacecraft autonomous data management where the spacecraft processes a large amount of raw data and extracts useful information, and autonomously executes or changes flights. The autonomous management of spacecraft uses modern control technologies such as artificial intelligence to establish a remote intelligent body on the spacecraft so that the spacecraft can complete its flight tasks by itself. Its goal is to accurately perceive its own state and external environment without relying on external information injection and control or rely on external control as little as possible. Divides the autonomous management level of spacecraft into two levels, autonomy and execution Covers the implementation of spacecraft autonomous management into three aspects, including autonomous health management of the spacecraft, mission management, and converting the mission into a specific sequence of instructions Discusses how these processes can take a large amount of raw data and extract useful information Covers the autonomous management model of the spacecraft, including compatibility
Autonomy for Marine Robots provides a timely and insightful overview of intelligent autonomy in marine robots. A brief history of this emerging field is provided, along with a discussion of the challenges unique to the underwater environment and their impact on the level of intelligent autonomy required. Topics covered at length examine advanced frameworks, path-planning, fault tolerance, machine learning, and cooperation as relevant to marine robots that need intelligent autonomy.
In the early 1990s, NASA Goddard Space Flight Center started researching and developing autonomous and autonomic ground and spacecraft control systems for future NASA missions. This research started by experimenting with and developing expert systems to automate ground station software and reduce the number of people needed to control a spacecraft. This was followed by research into agent-based technology to develop autonomous ground c- trol and spacecraft. Research into this area has now evolved into using the concepts of autonomic systems to make future space missions self-managing and giving them a high degree of survivability in the harsh environments in which they operate. This book describes much of the results of this research. In addition, it aimstodiscusstheneededsoftwaretomakefutureNASAspacemissionsmore completelyautonomousandautonomic.Thecoreofthesoftwareforthesenew missions has been written for other applications or is being applied gradually in current missions, or is in current development. It is intended that this book should document how NASA missions are becoming more autonomous and autonomic and should point to the way of making future missions highly - tonomous and autonomic. What is not covered is the supporting hardware of these missions or the intricate software that implements orbit and at- tude determination, on-board resource allocation, or planning and scheduling (though we refer to these technologies and give references for the interested reader).
This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Radical Agent Concepts, WRAC 2002, held in McLean, VA, USA in January 2002. The 32 revised full papers presented together with an invited article, 6 poster papers, and 2 panel reports were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on adaptation and learning, agent-based software engineering, agent architectures, agent communication and coordination, and innovative applications.
Abstract: "The Remote Agent (RA) is an Artificial Intelligence (AI) system which automates some of the tasks normally reserved for human mission operators and performs these tasks autonomously on-board the spacecraft. These tasks include activity generation, sequencing, spacecraft analysis, and failure recovery. The RA will be demonstrated as a flight experiment on Deep Space One (DS1), the first deep space mission of the NASA's New Millennium Program (NMP). As we moved from prototyping into actual flight code development and teamed with ground operators, we made several major extensions to the RA architecture to address the broader operational context in which RA would be used. These extensions support ground operators and the RA sharing a long-range mission profile with facilities for asynchronous ground updates; support ground operators monitoring and commanding the spacecraft at multiple levels of detail simultaneously; and enable ground operators to provide additional knowledge to the RA, such as parameter updates, model updates, and diagnostic information, without interfering with the activities of the RA or leaving the system in an inconsistent state. The resulting architecture supports incremental autonomy, in which a basic agent can be delivered early and then used in an increasingly autonomous manner over the lifetime of the mission. It also supports variable autonomy, as it enables ground operators to benefit from autonomy when they want it, but does not inhibit them from obtaining a detailed understanding and exercising tighter control when necessary. These issues are critical to the successful development and operation of autonomous spacecraft."
PAAMS, the International Conference on Practical Applications of Agents and Multi-Agent Systems is the international yearly tribune to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development of Agents and Multi-Agent Systems. This volume presents the papers that have been accepted for the 2011 edition. These articles capture the most innovative results and this year’s trends: Finance and Trading, Information Systems and Organisations, Leisure Culture and Interactions, Medicine and Cloud Computing, Platforms and Adaptation, Robotics and Manufacturing, Security and Privacy, Transports and Optimisation paper.
After a long period, in which the research focused mainly on industrial robotics, nowadays scientists aim to build machines able to act autonomously in unstructured domains, and to interface friendly with humans, while performing intelligently their assigned tasks. Such intelligent autonomous systems are now being intensively developed, and are ready to be applied to every field, from social life to modern enterprises. We believe the following years will be increasingly characterised by their extensive use. This is dramatically changing the whole scenario of human society.