Comparison of two strategies of path planning for underwater robot navigation under uncertainty

Zhang, T; Huang, S; Liu, D

Comparison of two strategies of path planning for underwater robot navigation under uncertainty

Zhang, T Huang, S

Liu, D

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Publication Type:: Conference Proceeding
Citation:: 2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014, 2014, pp. 901 - 906
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Zhang, T	en_US
dc.contributor.author	Huang, S https://orcid.org/0000-0002-6124-4178	en_US
dc.contributor.author	Liu, D https://orcid.org/0000-0002-1581-5582	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014, 2014, pp. 901 - 906	en_US
dc.identifier.isbn	9781479951994	en_US
dc.identifier.uri	http://hdl.handle.net/10453/33533
dc.description.abstract	© 2014 IEEE. This paper considers path planning for underwater robot in navigation tasks. The main challenge is how to deal with uncertainties in the underwater environment such as motion model error and sensing error. To overcome this challenge, two high level control methods have been presented and compared, which are based on the Model Predictive Control (MPC) strategy and the Partially Observable Markov Decision Process (POMDP) model, respectively. Navigation time, collision frequency, energy consumption and accuracy in localization are used as the assessment criteria for the two methods. It is shown that the MPC-based method is more efficient for our application scenarios while the POMDP-based method can provide more robust solutions.	en_US
dc.relation.ispartof	2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014	en_US
dc.relation.isbasedon	10.1109/ICARCV.2014.7064424	en_US
dc.title	Comparison of two strategies of path planning for underwater robot navigation under uncertainty	en_US
dc.type	Conference Proceeding
utslib.for	091303 Autonomous Vehicles	en_US
dc.location.activity	Singapore
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2014 IEEE. This paper considers path planning for underwater robot in navigation tasks. The main challenge is how to deal with uncertainties in the underwater environment such as motion model error and sensing error. To overcome this challenge, two high level control methods have been presented and compared, which are based on the Model Predictive Control (MPC) strategy and the Partially Observable Markov Decision Process (POMDP) model, respectively. Navigation time, collision frequency, energy consumption and accuracy in localization are used as the assessment criteria for the two methods. It is shown that the MPC-based method is more efficient for our application scenarios while the POMDP-based method can provide more robust solutions.

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http://hdl.handle.net/10453/33533