The paper describes ongoing integrated research on designing intelligent robots that can assist humans in making a situation assessment during Urban Search & Rescue (USAR) missions. These robots (rover, microcopter) are deployed during the early phases of an emergency response. The aim is to explore those areas of the disaster hotzone which are too dangerous or too difficult for a human to enter at that point. This requires the robots to be "intelligent" in the sense of being capable of various degrees of autonomy in acting and perceiving in the environment. At the same time, their intelligence needs to go beyond mere task-work. Robots and humans are inter-dependent. Human operators are dependent on these robots to provide information for a situation assessment. And robots are dependent on humans to help them operate (shared control) and perceive (shared assessment) in what are typically highly dynamic, largely unknown environments. Robots and humans need to form a team. The paper describes how various insights from robotics and Artificial Intelligence are combined, to develop new approaches for modeling human robot teaming. These approaches range from new forms of modeling situation awareness (to model distributed acting in dynamic space), human robot interaction (to model communication in teams), flexible planning (to model team coordination and joint action), and cognitive system design (to integrate different forms of functionality in a single system). Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

Designing intelligent robots for human-robot teaming in urban search & rescue / Kruijff, Geert Jan M; Colas, Francis; Svoboda, Tomáš; Van Diggelen, Jurriaan; Balmer, Patrick; PIRRI ARDIZZONE, Maria Fiora; Worst, Rainer. - SS-12-02:(2012), pp. 40-47. (Intervento presentato al convegno 2012 AAAI Spring Symposium tenutosi a Stanford, CA; USA nel 26-28 March 2012).

Designing intelligent robots for human-robot teaming in urban search & rescue

PIRRI ARDIZZONE, Maria Fiora;
2012

Abstract

The paper describes ongoing integrated research on designing intelligent robots that can assist humans in making a situation assessment during Urban Search & Rescue (USAR) missions. These robots (rover, microcopter) are deployed during the early phases of an emergency response. The aim is to explore those areas of the disaster hotzone which are too dangerous or too difficult for a human to enter at that point. This requires the robots to be "intelligent" in the sense of being capable of various degrees of autonomy in acting and perceiving in the environment. At the same time, their intelligence needs to go beyond mere task-work. Robots and humans are inter-dependent. Human operators are dependent on these robots to provide information for a situation assessment. And robots are dependent on humans to help them operate (shared control) and perceive (shared assessment) in what are typically highly dynamic, largely unknown environments. Robots and humans need to form a team. The paper describes how various insights from robotics and Artificial Intelligence are combined, to develop new approaches for modeling human robot teaming. These approaches range from new forms of modeling situation awareness (to model distributed acting in dynamic space), human robot interaction (to model communication in teams), flexible planning (to model team coordination and joint action), and cognitive system design (to integrate different forms of functionality in a single system). Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.
2012
2012 AAAI Spring Symposium
Artificial Intelligence
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Designing intelligent robots for human-robot teaming in urban search & rescue / Kruijff, Geert Jan M; Colas, Francis; Svoboda, Tomáš; Van Diggelen, Jurriaan; Balmer, Patrick; PIRRI ARDIZZONE, Maria Fiora; Worst, Rainer. - SS-12-02:(2012), pp. 40-47. (Intervento presentato al convegno 2012 AAAI Spring Symposium tenutosi a Stanford, CA; USA nel 26-28 March 2012).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/951465
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