Elly Winner

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Planning actions for real robots in dynamic and uncertain environments is a challenging problem. Using a complete model of the world is not viable and an integration of deliberation and behavior-based re-active planning is most appropriate for goal achievement and uncertainty handling. This paper reports on our successful development of a system integrating(More)
Our work is driven by one of the core purposes of artificial intelligence: to develop real robotic agents that achieve complex high-level goals in real-time environments. Robotic behaviors select actions as a function of the state of the robot and of the world. Designing robust and appropriate robotic behaviors is a difficult because of noise, uncertainty(More)
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