| Autor: |
Mauro Gaggero, Donato Di Paola, Antonio Petitti, Luca Caviglione |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 7, Pp 11246-11257 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2019.2892310 |
| Popis: |
Future cyber-physical systems are expected to exploit autonomous robots to accomplish dangerous or complex missions composed of several tasks. A critical aspect is the availability of suitable mission planning strategies to react against external disturbances or hardware outages. Unfortunately, classic planning approaches may not take advantage of the ability of cyber-physical systems to collect a variety of information from sensors or IoT nodes, which can be used to forecast future events. Therefore, this paper proposes the adoption of predictive control for mission planning. Specifically, predictive control is used to compute online the best time instants when to change the assignment of tasks to robots by solving finite-horizon optimal control problems. The simulation results performed in comparison with “legacy” reactive and proactive strategies showcase the superiority of the proposed approach, especially in scenarios characterized by large disturbances. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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