Model-based programming of intelligent embedded systems and robotic space explorers

Williams, Brian; Ingham, Michel D.; Chung, Seung; Elliott, Paul

doi:10.1109/jproc.2002.805828

Cited by 122 publications

(64 citation statements)

References 16 publications

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“…A descendant of RAP is the language Reactive Plan Language (RPL) which was designed by [14] to incorporate a richer set of control constructs and to allow the creation of reactive plans for robotic agents. Further plan execution systems used by autonomous robots are the Reactive Model-based Programming Language (RMPL) [24] and the Executive Support Language (ESL) [10].…”

Section: Related Workmentioning

confidence: 99%

RoboEarth Action Recipe Execution

Marco¹,

Tenorth²,

Häußermann³

et al. 2013

Frontiers of Intelligent Autonomous Systems

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The ability of reusing existing task execution plans is an important step towards autonomous behavior. Today, the reuse of sophisticated services allowing robots to act autonomous is usually limited to identical robot platforms and to very similar application scenarios. The approach presented in this paper proposes a way to mitigate this limitation by storing and reusing task plans on a global accessible database. We describe the task execution engine for the RoboEarth project [26] to demonstrate its ability to execute tasks in a flexible and reliable way.

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Section: Related Workmentioning

confidence: 99%

RoboEarth Action Recipe Execution

Marco¹,

Tenorth²,

Häußermann³

et al. 2013

Frontiers of Intelligent Autonomous Systems

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“…The paper suggests that an emphasis should be placed on developing techniques to enable software to recognize that it has failed and to recover from the failure. Their technique lies in the use of a Reactive Model-based Programming Language (RMPL) [54] for D R A F T specifying both correct and faulty behavior of the software components. They also use high-level control programs [55] for guiding the system to the desirable behaviors.…”

Section: Comparison-based Anomaly Detectionmentioning

confidence: 99%

Deliberative, search-based mitigation strategies for model-based software health management

Mahadevan

Dubey

Balasubramanian

et al. 2013

Innovations Syst Softw Eng

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Rising software complexity in aerospace systems makes them very difficult to analyze and prepare for all possible fault scenarios at design-time, therefore classical run-time fault-tolerance techniques, such as self-checking pairs and triple modular redundancy are used. However, several recent incidents have made it clear that existing software fault tolerance techniques alone are not sufficient. To improve system dependability, simpler, yet formally specified and verified run-time monitoring, diagnosis, and fault mitigation capabilities are needed. Such architectures are already in use for managing the health of vehicles and systems. Software health management is the application of these techniques to software systems. In this paper we briefly describe the software health management techniques and architecture developed by our research group. The foundation of the architecture is a real-time component framework (built upon ARINC-653 platform services) that defines a model of computation for software components. Dedicated architectural elements: the Component Level Health Manager (CLHM) and System Level Health Manager (SLHM) provide the health management services: anomaly detection, fault source isolation, and fault mitigation. The SLHM includes a diagnosis engine that (1) uses a Timed Failure Propagation (TFPG) model derived from the component assembly model, (2) reasons about cascading fault effects in the system, and (3) isolates the fault source component(s). Thereafter, the appropriate system level mitigation action is taken. The main focus of this article is the description of the fault mitigation architecture that uses goal-based deliberative reasoning to determine the best mitigation actions for recovering the system from the identified failure mode.

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“…PRS [7], TDL [20] and Architecture for Autonomy [1] focus on the design and implementation of plan execution languages that incorporate failure monitoring and recovery as well as concurrent execution. Williams et al [25] developed the Reactive Model-based Programming Language (RMPL) to represent reactive plans, however the plans are not explicit and transparent. One of the best-known reactive planning languages is RAP [5] which is very robust and can also monitor the desired and actual outcome of the given plan.…”

Section: Introductionmentioning

confidence: 99%

Structured reactive controllers and transformational planning for manufacturing

Rühr

Pangercic

Beetz

2008

2008 IEEE International Conference on Emerging Technologies and Factory Automation

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While current manufacturing systems are built to avoid uncertainty, the increase of setup reconfiguration frequency and ever higher numbers of variants produced on the same systems motivate the exploration of new approaches to manufacturing and manufacturing control. In this paper we discuss the application of plan based controllers and transformational planning in manufacturing. Autonomous control techniques are used to create flexible, robust and adaptive behaviour in the artificial intelligence community for about 20 years. In order to show the applicability and adequacy of plan based control in manufacturing, we examplify the approach in a Flexible Manufacturing System (FMS). The experiments show that significant performance boosts are possible through transformational planning.

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Model-based programming of intelligent embedded systems and robotic space explorers

Abstract: Programming complex embedded systems involves reasoning

Cited by 122 publications

References 16 publications

RoboEarth Action Recipe Execution

RoboEarth Action Recipe Execution

Deliberative, search-based mitigation strategies for model-based software health management

Structured reactive controllers and transformational planning for manufacturing

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