Titre non précisé

old_uid9760
titleTitre non précisé
start_date2011/03/08
schedule14h
onlineno
location_infopyramide ISIR (55/65)
summaryThe main goal of our current research is the design of a behavior-based robotic architecture that has the capability of adapting behaviors activations both to the rate of change of the environment and to changes of its internal states. For this purpose, attentional mechanisms, balancing sensors elaboration and actions execution, can play a crucial role. In particular, attentional processes play two main roles: direct sensors towards the most salient sources of information; filter the available sensory data to prevent unnecessary information processing. As a result of the application of these mechanisms, the robot should react faster and more effectively to task-related or safety critical stimuli because processing resources are not wasted with non relevant stimuli. Attentional mechanisms applied to autonomous robotic systems have been proposed elsewhere, mainly for vision based robotics. In contrast, in our work, we are interested in artificial attentional processes suitable for the executive control. In particular, our aim is to provide a kind of supervisory attentional system capable of monitoring and regulating multiple concurrent behaviors at different level of abstraction. We present an attentional system for a robotic agent capable of adapting its emergent behavior to the surrounding environment and to its internal state. In this framework, the agent is endowed with simple attentional mechanisms regulating the frequencies of sensory readings and behavior activations. The process of changing the frequency of sensory readings is interpreted as an increase or decrease of attention towards relevant behaviors and particular aspects of the external environment. Here, we present our framework providing several case studies where we discuss the effectiveness of the approach considering its scalability and the adaptivity with respect to different environments and tasks.
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