PANDORA: Persistent Autonomy through Learning, Adaptation, Observation and Re-planning

David Michael Lane, Francesco Maurelli, Thomas Larkworthy, Darwin Caldwell, Joaquim Salvi, Maria Fox, Kostas Kyriakopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

Autonomous robots are not very good at being autonomous. Operating in real environments, they easily get stuck, often ask for help, and generally succeed only when attempting simple tasks in well-known situations. PANDORA is a three year project that will develop and evaluate new computational methods to make underwater robots Persistently Autonomous, significantly reducing the frequency of assistance requests. The key to this is an ability to recognise failure and respond to it, at all levels of abstraction and time constant. Under the guidance of major industrial players, validation tasks of Inspection, cleaning and valve turning will be trialled with partners’ AUVs in Scotland and Spain.
Original languageEnglish
Title of host publicationProc IFAC Int Conference on Navigation, Guidance and Control of Underwater Vehicles, Porto, Portugal
PublisherInternational Federation of Automatic Control (IFAC)
Publication statusPublished - 10 Apr 2012

Fingerprint Dive into the research topics of 'PANDORA: Persistent Autonomy through Learning, Adaptation, Observation and Re-planning'. Together they form a unique fingerprint.

  • Cite this

    Lane, D. M., Maurelli, F., Larkworthy, T., Caldwell, D., Salvi, J., Fox, M., & Kyriakopoulos, K. (2012). PANDORA: Persistent Autonomy through Learning, Adaptation, Observation and Re-planning. In Proc IFAC Int Conference on Navigation, Guidance and Control of Underwater Vehicles, Porto, Portugal International Federation of Automatic Control (IFAC).