DocumentCode :
2469254
Title :
An attentive multi-sensor based system for mobile robotics
Author :
Colombini, Esther Luna ; Ribeiro, Carlos Henrique Costa
Author_Institution :
Dept. of Comput. Sci., Technol. Inst. of Aeronaut., São José dos Campos, Brazil
fYear :
2012
fDate :
14-17 Oct. 2012
Firstpage :
1509
Lastpage :
1514
Abstract :
Usually embodied in real environments, robots are expected to perceive and act in their surrounding world in a human-like fashion [1], through perception, reasoning, planning and decision making processes. Although high computational power is available nowadays, the complexity of real scenes - continuous, partially unknown and usually unpredictable - can not be taken for granted. To actively act in this environment, robots are fully equipped with an enormous amount of sensors, overwhelming them with an immense amount of data that can not fully be processed and that constantly changes across time and space. To overcome this problem, the natural human filter - Attention - could be used as inspiration. This paper proposes an architecture that supports a transfer of domain from visual models to a robotics domain that uses sensors such as range scanners and sonars. Furthermore, it discusses the possibility of using multiple sensors to define multiple features. The experiments were performed in a simulated high fidelity environment and results have shown that the model proposed can account for detecting salient stimuli according to the modeled features.
Keywords :
mobile robots; sensor fusion; attentive multisensor based system; mobile robotics; range scanners; salient stimuli detection; sonars; visual models; Feature extraction; Mathematical model; Robot kinematics; Robot sensing systems; Sonar; Attention; Bottom-up Attention; Multi-Sensor; Range Scanner; Robotics; Saliency Models; Sonar;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4673-1713-9
Electronic_ISBN :
978-1-4673-1712-2
Type :
conf
DOI :
10.1109/ICSMC.2012.6377949
Filename :
6377949
Link To Document :
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