Imperial College London

DrPetarKormushev

Faculty of EngineeringDyson School of Design Engineering

Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 9235p.kormushev Website

 
 
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Location

 

10-12 Prince's GardensSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Ahmadzadeh:2013,
author = {Ahmadzadeh, SR and Leonetti, M and Kormushev, P},
title = {Online Direct Policy Search for Thruster Failure Recovery in Autonomous Underwater Vehicles},
url = {http://kormushev.com/papers/Ahmadzadeh_ERLARS-2013.pdf},
year = {2013}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - Autonomous underwater vehicles are prone to variousfactors that may lead a mission to fail and cause unrecoverable damages.Even robust controllers cannot make sure that the robot is ableto navigate to a safe location in such situations. In this paper wepropose an online learning method for reconfiguring the controller,which tries to recover the robot and survive the mission using thecurrent asset of the system. The proposed method is framed in thereinforcement learning setting, and in particular as a model-baseddirect policy search approach. Since learning on a damaged vehiclewould be impossible owing to time and energy constraints, learningis performed on a model which is identified and kept updatedonline. We evaluate the applicability of our method with differentpolicy representations and learning algorithms, on the model of thevehicle Girona500.
AU - Ahmadzadeh,SR
AU - Leonetti,M
AU - Kormushev,P
PY - 2013///
TI - Online Direct Policy Search for Thruster Failure Recovery in Autonomous Underwater Vehicles
UR - http://kormushev.com/papers/Ahmadzadeh_ERLARS-2013.pdf
UR - http://hdl.handle.net/10044/1/26101
ER -