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Automatically Composing and Parameterizing Skills by Evolving Finite State Automata

Riano, Lorenzo and McGinnity, TM (2012) Automatically Composing and Parameterizing Skills by Evolving Finite State Automata. Robotics and Autonomous Systems, 60 (4). pp. 639-650. [Journal article]

PDF - Accepted Version

URL: http://dx.doi.org/10.1016/j.robot.2012.01.002

DOI: 10.1016/j.robot.2012.01.002


We propose a robotics algorithm that is able to simultaneously combine, adapt and create actions to solve a task. The actions are combined in a Finite State Automaton whose structure is determined by a novel evolutionary algorithm. The actions parameters, or new actions, are evolved alongside the FSA topology. Actions can be combined together in a hierarchical fashion. This approach relies on skills that with which the robot is already provided, like grasping or motion planning. Therefore software reuse is an important advantage of our proposed approach. We conducted several experiments both in simulation and on a real mobile manipulator PR2 robot, where skills of increasing complexity are evolved. Our results show that i) an FSA generated in simulation can be directly applied to a real robot without modifications and ii) the evolved FSA is robust to the noise and the uncertainty arising from real-world sensors.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:20839
Deposited By: Dr Lorenzo Riano
Deposited On:30 Jan 2012 15:09
Last Modified:17 Oct 2017 16:01

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