Name
Abstract | ||
|---|---|---|
In the robotics domain, the state of the world may change in unexpected ways during execution of a task. From a planning perspective, these discrepancies may render the currently executed plan invalid and thus need to be detected as soon as possible. We tackle this problem by translating the problem of plan execution monitoring to a runtime verification problem. We propose a template based framework that allows detecting changes of the state during both plan generation and plan execution. We integrated our approach into a domain-independent platform for planning, executing, and monitoring. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-40846-5_45 | HYBRID ARTIFICIAL INTELLIGENT SYSTEMS |
Field | DocType | Volume |
Software engineering,Computer science,Runtime verification,Linear temporal logic,Artificial intelligence,Temporal logic,Planetary rover,Machine learning,Robotics | Conference | 8073 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
20 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thomas Reinbacher | 1 | 70 | 7.21 |
| César Guzmán-Alvarez | 2 | 0 | 0.68 |