Symbolic Boolean manipulation with ordered binary-decision diagrams
ACM Computing Surveys (CSUR)
Model checking
Construction of Abstract State Graphs with PVS
CAV '97 Proceedings of the 9th International Conference on Computer Aided Verification
Weak, strong, and strong cyclic planning via symbolic model checking
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
Counterexample-guided abstraction refinement for symbolic model checking
Journal of the ACM (JACM)
Automated Planning: Theory & Practice
Automated Planning: Theory & Practice
A Practical Introduction to PSL (Series on Integrated Circuits and Systems)
A Practical Introduction to PSL (Series on Integrated Circuits and Systems)
Generating safe assumption-based plans for partially observable, nondeterministic domains
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Model-based monitoring and diagnosis of systems with software-extended behavior
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Formal verification of diagnosability via symbolic model checking
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Strong planning under partial observability
Artificial Intelligence
A model-based approach to reactive self-configuring systems
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
SMT techniques for fast predicate abstraction
CAV'06 Proceedings of the 18th international conference on Computer Aided Verification
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Deep space missions are characterized by severely constrained communication links. To meet the needs of future missions and increase their scientific return, future space systems will require an increased level of autonomy on-board. In this work, we propose a comprehensive approach to on-board autonomy relying on model-based reasoning, and encompassing many important reasoning capabilities such as plan generation, validation, execution and monitoring, FDIR, and run-time diagnosis. The controlled platform is represented symbolically, and the reasoning capabilities are seen as symbolic manipulation of such formal model. We have developed a prototype of our framework, implemented within an on-board Autonomous Reasoning Engine. We have evaluated our approach on two case-studies inspired by real-world, ongoing projects, and characterized it in terms of reliability, availability and performance.