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Annual Report 2002 - Örebro universitet

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<strong>Annual</strong> <strong>Report</strong> <strong>2002</strong> 43<br />

Project: Generating and Executing Plans under Uncertainty<br />

Project leader: Lars Karlsson<br />

Project staff: Abdelbaki Bouguerra<br />

Funding: KK Foundation, Faculty funding, EU funding via the PLANET Network.<br />

Cooperation: PLANET, European Network of Excellence in AI Planning.<br />

Synopsis:<br />

An intelligent mobile robot both needs to react quickly to changing conditions and to<br />

formulate and implement plans to achieve its more long-term objectives. From the robot's<br />

perspective, there are a number of sources of uncertainty that complicate its planning and<br />

acting, including other agents and dynamical processes, incomplete a priori information,<br />

restricted and unreliable sensing capabilities, and the uncertainty inherent the robot's own<br />

actions. Fuzzy logic is an interesting tool for taking these sources of uncertainty into account,<br />

as well as for estimating the quality and success of plans. Within this context, we<br />

investigate issues such as how to represent and reason about actions, sensing, and complex<br />

plans, how to integrate deliberation and acting, and how to detect when a plan is not going<br />

well or when better opportunities arise.<br />

Main results in <strong>2002</strong>:<br />

- A grant of about 1,8 MSEK has been awarded by Vetenskapsrådet to this project for the<br />

period 2003-2005.<br />

- Paper published in the edited volume "Plan-Based Control of Robotic Agents" (Springer,<br />

Germany, <strong>2002</strong>).<br />

- Msc thesis by Tommaso Schiavinotto (visiting student at AASS in 2001) defended at the<br />

University of Pisa, Italy.<br />

Future developments:<br />

- Work will focus on the project objective defined in the application funded by<br />

Vetenskaprådet.<br />

- A new PhD student (Abdelbaki Bouguerra) has been enrolled and will work on this<br />

project.<br />

Project: Anchoring Symbols to Sensor Data<br />

Project leader: Silvia Coradeschi<br />

Project staff: Alessandro Saffiotti, Kevin LeBlanc<br />

Funding: KK Foundation, Faculty funding, Vetenskapsrådet<br />

Cooperation: University of Palermo, Italy<br />

Synopsis:<br />

Intelligent agents embedded in physical environments need the ability to connect, or anchor,<br />

the symbols used to perform abstract reasoning to the physical entities which these symbols<br />

refer to. Anchoring must deal with indexical and objective references, definite and indefinite<br />

identifiers, and temporary impossibility to percept physical entities. Furthermore it needs to

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