Post date: May 29, 2016 5:3:55 PM
Seyed Reza Ahmadzadeh, Petar Kormushev, Darwin G. Caldwell
Reference:
Seyed Reza Ahmadzadeh, Petar Kormushev, Darwin G. Caldwell, "Autonomous Robotic Valve Turning: A
Hierarchical Learning Approach", In Proc. IEEE Intl Conf. on Robotics and Automation, (ICRA 2013),
Karlsruhe, Germany, pp. 4614-4619, 6-11 May 2013.
Bibtex Entry:
@INPROCEEDINGS{ahmadzadeh2013autonomous, TITLE={Autonomous Robotic Valve Turning: A Hierarchical Learning Approach}, AUTHOR={Ahmadzadeh, Seyed Reza and Kormushev, Petar and Caldwell, Darwin G.}, BOOKTITLE={Robotics and Automation ({ICRA}), {IEEE} International Conference on}, PAGES={4614--4619}, YEAR={2013}, MONTH={May}, ORGANIZATION={IEEE}, ADDRESS={Karlsruhe,Germany}, DOi={10.1109/ICRA.2013.6631235} }
DOI:
Abstract:
Autonomous valve turning is an extremely challenging task for an Autonomous Underwater Vehicle
(AUV). To resolve this challenge, this paper proposes a set of different computational techniques
integrated in a three-layer hierarchical scheme. Each layer realizes specific subtasks to improve
the persistent autonomy of the system. In the first layer, the robot acquires the motor skills of
approaching and grasping the valve by kinesthetic teaching. A Reactive Fuzzy Decision Maker (RFDM)
is devised in the second layer which reacts to the relative movement between the valve and the AUV,
and alters the robot's movement accordingly. Apprenticeship learning method, implemented in the
third layer, performs tuning of the RFDM based on expert knowledge. Although the long-term goal is
to perform the valve turning task on a real AUV, as a first step the proposed approach is tested in
a laboratory environment.