348,523 research outputs found
Methodological Flaws in Cognitive Animat Research
In the field of convergence between research in autonomous machine construction and biological systems understanding it is usually argued that building robots for research on auton- omy by replicating extant animals is a valuable strategy for engineering autonomous intelligent systems. In this paper we will address the very issue of animat construction, the ratio- nale behind this, their current implementations and the value they are producing. It will be shown that current activity, as it is done today, is deeply flawed and useless as research in the science and engineering of autonomy
Agent Based Approaches to Engineering Autonomous Space Software
Current approaches to the engineering of space software such as satellite
control systems are based around the development of feedback controllers using
packages such as MatLab's Simulink toolbox. These provide powerful tools for
engineering real time systems that adapt to changes in the environment but are
limited when the controller itself needs to be adapted.
We are investigating ways in which ideas from temporal logics and agent
programming can be integrated with the use of such control systems to provide a
more powerful layer of autonomous decision making. This paper will discuss our
initial approaches to the engineering of such systems.Comment: 3 pages, 1 Figure, Formal Methods in Aerospac
Activities of the Space Advanced Research Team at the University of Glasgow
A wide range of technologies and methodologies for space systems engineering are currently being developed at the University of Glasgow. Much of the work is centred on mission analysis and trajectory optimisation, complemented by research activities in autonomous and multi-agent systems. This paper will summarise these activities to provide a broad overview of the current research interests of the Space Advanced Research Team (SpaceART). It will be seen that although much of the work is mission driven and focussed on possible future applications, some activities represent basic research in space systems engineering
Engineering an Ontology for Autonomous Systems - The OASys Ontology
This paper describes the development of an ontology for autonomous systems, as the initial stage of a research programe on autonomous systemsâ engineering within a model-based control approach. The ontology aims at providing a uniïŹed conceptual framework for the autonomous systemsâ stakeholders, from developers to software engineers. The modular ontology contains both generic and domain-speciïŹc concepts for autonomous systems description and engineering. The ontology serves as the basis in a methodology to obtain the autonomous systemâs conceptual models. The objective is to obtain and to use these models as main input for the autonomous systemâs model-based control system
Autonomous Boat Control Software Design Using Model-Based Systems Engineering
While there is considerable buzz about self-driving cars, self-driving boats are actually more fully developed. The Boat Hardware Control Platform Team was tasked with developing a fleet of small autonomous boats that travel to a destination while avoiding obstacles and staying in formation. The authorâs specific task was to develop software used by the boats to detect obstacles and plan a route to a destination. This was done using a method inspired by self-driving cars, which shows promise, but is still being tested at the time of writing. The entire project incorporated model-based systems engineering, which proved to be useful
Adapting Quality Assurance to Adaptive Systems: The Scenario Coevolution Paradigm
From formal and practical analysis, we identify new challenges that
self-adaptive systems pose to the process of quality assurance. When tackling
these, the effort spent on various tasks in the process of software engineering
is naturally re-distributed. We claim that all steps related to testing need to
become self-adaptive to match the capabilities of the self-adaptive
system-under-test. Otherwise, the adaptive system's behavior might elude
traditional variants of quality assurance. We thus propose the paradigm of
scenario coevolution, which describes a pool of test cases and other
constraints on system behavior that evolves in parallel to the (in part
autonomous) development of behavior in the system-under-test. Scenario
coevolution offers a simple structure for the organization of adaptive testing
that allows for both human-controlled and autonomous intervention, supporting
software engineering for adaptive systems on a procedural as well as technical
level.Comment: 17 pages, published at ISOLA 201
Knowledge-based Autonomous Test Engineer (KATE)
Mathematical models of system components have long been used to allow simulators to predict system behavior to various stimuli. Recent efforts to monitor, diagnose, and control real-time systems using component models have experienced similar success. NASA Kennedy is continuing the development of a tool for implementing real-time knowledge-based diagnostic and control systems called KATE (Knowledge based Autonomous Test Engineer). KATE is a model-based reasoning shell designed to provide autonomous control, monitoring, fault detection, and diagnostics for complex engineering systems by applying its reasoning techniques to an exchangeable quantitative model describing the structure and function of the various system components and their systemic behavior
Autonomous Payload Design with Systems Engineering
The design will be an autonomous payload consisting of auto deployment of a drone running an autonomous mission of mapping the terrain around a grounded rocket. The project is part of the Akronauts payload project for the 2022 Spaceport competition. It will include the development of a ground station for monitoring and controlling the drone and the transfer of live data to the station and a computer on board the rocket. The project will aim to use system engineering techniques to accomplish this in the hope of providing documentation and thus insight into the best way to develop a multi-disciplinary payload to future Akronauts payload projects
NASA Center for Intelligent Robotic Systems for Space Exploration
NASA's program for the civilian exploration of space is a challenge to scientists and engineers to help maintain and further develop the United States' position of leadership in a focused sphere of space activity. Such an ambitious plan requires the contribution and further development of many scientific and technological fields. One research area essential for the success of these space exploration programs is Intelligent Robotic Systems. These systems represent a class of autonomous and semi-autonomous machines that can perform human-like functions with or without human interaction. They are fundamental for activities too hazardous for humans or too distant or complex for remote telemanipulation. To meet this challenge, Rensselaer Polytechnic Institute (RPI) has established an Engineering Research Center for Intelligent Robotic Systems for Space Exploration (CIRSSE). The Center was created with a five year $5.5 million grant from NASA submitted by a team of the Robotics and Automation Laboratories. The Robotics and Automation Laboratories of RPI are the result of the merger of the Robotics and Automation Laboratory of the Department of Electrical, Computer, and Systems Engineering (ECSE) and the Research Laboratory for Kinematics and Robotic Mechanisms of the Department of Mechanical Engineering, Aeronautical Engineering, and Mechanics (ME,AE,&M), in 1987. This report is an examination of the activities that are centered at CIRSSE
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