PANDORA: Persistent autonomy through learning, adaptation, observation and re-planning

David M. Lane; Francesco Maurelli; Tom Larkworthy; Darwin Caldwell; Joaquim Salvi; Maria Fox; Konstantinos Kyriakopoulos

doi:10.3182/20120410-3-pt-4028.00061

PANDORA: Persistent autonomy through learning, adaptation, observation and re-planning

David M. Lane, Francesco Maurelli, Tom Larkworthy, Darwin Caldwell, Joaquim Salvi, Maria Fox, Konstantinos Kyriakopoulos

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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 language	English (US)
Title of host publication	IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2012
Publisher	IFAC Secretariat
Pages	367-372
Number of pages	6
Edition	PART 1
ISBN (Print)	9783902823199
DOIs	https://doi.org/10.3182/20120410-3-pt-4028.00061
State	Published - 2012
Event	3rd IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2012 - Porto, Portugal Duration: Apr 10 2012 → Apr 12 2012

Publication series

Name	IFAC Proceedings Volumes (IFAC-PapersOnline)
Number	PART 1
Volume	3
ISSN (Print)	1474-6670

Conference

Conference	3rd IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2012
Country/Territory	Portugal
City	Porto
Period	4/10/12 → 4/12/12

ASJC Scopus subject areas

Control and Systems Engineering

Access to Document

10.3182/20120410-3-pt-4028.00061

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 IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2012 (PART 1 ed., pp. 367-372). (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 3, No. PART 1). IFAC Secretariat. https://doi.org/10.3182/20120410-3-pt-4028.00061

PANDORA: Persistent autonomy through learning, adaptation, observation and re-planning. / Lane, David M.; Maurelli, Francesco; Larkworthy, Tom et al.
IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2012. PART 1. ed. IFAC Secretariat, 2012. p. 367-372 (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 3, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lane, DM, Maurelli, F, Larkworthy, T, Caldwell, D, Salvi, J, Fox, M & Kyriakopoulos, K 2012, PANDORA: Persistent autonomy through learning, adaptation, observation and re-planning. in IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2012. PART 1 edn, IFAC Proceedings Volumes (IFAC-PapersOnline), no. PART 1, vol. 3, IFAC Secretariat, pp. 367-372, 3rd IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2012, Porto, Portugal, 4/10/12. https://doi.org/10.3182/20120410-3-pt-4028.00061

Lane DM, Maurelli F, Larkworthy T, Caldwell D, Salvi J, Fox M et al. PANDORA: Persistent autonomy through learning, adaptation, observation and re-planning. In IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2012. PART 1 ed. IFAC Secretariat. 2012. p. 367-372. (IFAC Proceedings Volumes (IFAC-PapersOnline); PART 1). doi: 10.3182/20120410-3-pt-4028.00061

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PANDORA: Persistent autonomy through learning, adaptation, observation and re-planning

Abstract

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ASJC Scopus subject areas

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