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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Duarte, M., Oliveira, S. M. & Christensen, A. L. (2015). Evolution of hybrid robotic controllers for complex tasks. Journal of Intelligent and Robotic Systems. 78 (3-4), 463-484
Exportar Referência (IEEE) 
M. A. Duarte et al.,  "Evolution of hybrid robotic controllers for complex tasks", in Journal of Intelligent and Robotic Systems, vol. 78, no. 3-4, pp. 463-484, 2015
Exportar BibTeX 
@article{duarte2015_1732210647568,
	author = "Duarte, M. and Oliveira, S. M. and Christensen, A. L.",
	title = "Evolution of hybrid robotic controllers for complex tasks",
	journal = "Journal of Intelligent and Robotic Systems",
	year = "2015",
	volume = "78",
	number = "3-4",
	doi = "10.1007/s10846-014-0086-x",
	pages = "463-484",
	url = "http://link.springer.com/article/10.1007/s10846-014-0086-x"
}
Exportar RIS 
TY  - JOUR
TI  - Evolution of hybrid robotic controllers for complex tasks
T2  - Journal of Intelligent and Robotic Systems
VL  - 78
IS  - 3-4
AU  - Duarte, M.
AU  - Oliveira, S. M.
AU  - Christensen, A. L.
PY  - 2015
SP  - 463-484
SN  - 0921-0296
DO  - 10.1007/s10846-014-0086-x
UR  - http://link.springer.com/article/10.1007/s10846-014-0086-x
AB  - We propose an approach to the synthesis of hierarchical control systems comprising both evolved and manually programmed control for autonomous robots. We recursively divide the goal task into sub-tasks until a solution can be evolved or until a solution can easily be programmed by hand. Hierarchical composition of behavior allows us to overcome the fundamental challenges that typically prevent evolutionary robotics from being applied to complex tasks: bootstrapping the evolutionary process, avoiding deception, and successfully transferring control evolved in simulation to real robotic hardware. We demonstrate the proposed approach by synthesizing control systems for two tasks whose complexity is beyond state of the art in evolutionary robotics. The first task is a rescue task in which all behaviors are evolved. The second task is a cleaning task in which evolved behaviors are combined with a manually programmed behavior that enables the robot to open doors in the environment. We demonstrate incremental transfer of evolved control from simulation to real robotic hardware, and we show how our approach allows for the reuse of behaviors in different tasks.

ER  -