scholarly journals Systems Engineering and Architecting for Intelligent Autonomous Systems

2016 ◽  
pp. 313-351
Author(s):  
Sagar Behere ◽  
Martin Törngren
Author(s):  
Adhiti T. Raman ◽  
Venkat N. Krovi ◽  
Matthias J. A. Schmid

A new class of distributed, autonomous systems is emerging, capable of exploiting multimodal distributed and networked spatial and temporal data (at significantly larger scales). A renaissance autonomy engineer requires proficiency in both traditional engineering concepts as well as a systems engineering skillset for implementing the ensuing complex systems. In this paper, we describe goals, development and first offering of a scaffolded course: “AuE 893 Autonomy: Science and Systems” to begin addressing this goal. Geared towards graduate engineering students, with limited prior exposure, the course complements the concepts from traditional courses (on mobile-robotics) with experiential hands-on system-integration efforts (building on the F1tenth.org kits). The staged course structure initially builds upon open-source Robotics Operating System (ROS) tutorials on simulated systems (Gazebo/RViz) with networked communication; Hardware-in-the-loop realization (with a Turtlebot platform) then aids the exploration (and reinforcement) of autonomy concepts. The course culminates in a final-project comprising performance testing with student-team integrated scaled Autonomous Remote Control cars (based on the F1tenth.org parts-list). All three student teams were successful in navigating around a closed racecourse at speeds of 10–15 miles per hour, using Simultaneous Localization and Mapping (SLAM) for situational awareness and obstacle-avoidance. We conclude with discussion of lessons-learnt and opportunities for future improvement.


Author(s):  
Christopher Sconyers ◽  
Young-Ki Lee ◽  
Kilsoo Kim ◽  
Sehwan Oh ◽  
Dimitri Mavris ◽  
...  

This paper introduces a methodology for the design, testing and assessment of incipient failure detection techniques for failing components/systems of critical engineered systems/processes masked or hidden by feedback control loops. It is recognized that the optimum operation of critical assets (aircraft, autonomous systems, industrial processes, etc.) may be compromised by feedback control loops, which mask severe fault modes while compensating for typical disturbances. Detrimental consequences of such occurrences include the inability to detect expeditiously and accurately incipient failures, loss of control, and inefficient operation of assets in the form of fuel overconsumption and adverse environmental impact. A novel control-theoretic framework is presented to address the masking problem. Major elements of the proposed approach are employed in simulation to develop, implement and validate how faults are distinguished from disturbances and how faults are detected and identified with performance guarantees, i.e., prescribed confidence level and given false alarm rate.The demonstration and validity of the tools/methods employed necessitates, in addition to the theoretical content, a suitable testbed. We have employed and describe briefly in this paper an autonomous hovercraft as the test prototype. We pursue a systems engineering process to design, construct and test the prototype hovercraft instrumented appropriately for purposes of fault injection, monitoring and the presence of control loops. We emphasize a general control-theoretic framework to the masking problem and utilize a simulation environment to derive results and illustrate the efficacy of the methodology.


Author(s):  
H Figueiredo ◽  
D Cook ◽  
W Biggs

Intelligent autonomous systems (IAS) are set to become a feature of future defence programmes, and their introduction will pose challenges to traditional systems engineering and acquisition practice. Whilst the need for operational and technical assurance will endure, the need to manage programmes that deliver iteratively and which are continually evolving requires fresh thinking. New increments may well be undergoing acceptance testing against a backdrop of continual developments to higher level concepts of operation – there may be no stable baseline. Furthermore, the unbounded and potentially non-deterministic nature of IAS means testing alone is unlikely to provide satisfactory assurance, especially for systems that are able to learn from previous mission data. Lastly, at the very core of what is referred to as human-autonomy teaming is a notion of trust by the operator of the IAS, a trust which builds through development, integration, training and deployment, implying a blurring of boundaries between that which is technical assurance and that which is operational. In response to these challenges, QinetiQ are investing in UK test and evaluation infrastructure and developing, with partners, approaches that will mitigate the risks posed by these new technologies. As outlined in this paper, these include distributed live, virtual and constructive facilities, brokered policy enforcement by software and developing a body of trusted software components. The paper argues how these developments address the identified challenges, highlighting remaining gaps and drawing on evidence from ongoing UK MOD research and development; it concludes with the approaching investment and programmatic choices that will need to be made to ensure best-for-enterprise outcomes.


2020 ◽  
Vol 43 ◽  
Author(s):  
Valerie F. Reyna ◽  
David A. Broniatowski

Abstract Gilead et al. offer a thoughtful and much-needed treatment of abstraction. However, it fails to build on an extensive literature on abstraction, representational diversity, neurocognition, and psychopathology that provides important constraints and alternative evidence-based conceptions. We draw on conceptions in software engineering, socio-technical systems engineering, and a neurocognitive theory with abstract representations of gist at its core, fuzzy-trace theory.


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