TY - GEN
T1 - Integrating a closed world planner with an open world robot
T2 - 24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference, AAAI-10 / IAAI-10
AU - Talamadupula, Kartik
AU - Benton, J.
AU - Schermerhorn, Paul
AU - Kambhampati, Subbarao
AU - Scheutz, Matthias
PY - 2010/1/1
Y1 - 2010/1/1
N2 - In this paper, we present an integrated planning and robotic architecture that actively directs an agent engaged in an urban search and rescue (USAR) scenario. We describe three salient features that comprise the planning component of this system, namely (1) the ability to plan in a world open with respect to objects, (2) execution monitoring and replanning abilities, and (3) handling sof t goals, and detail the interaction of these parts in representing and solving the USAR scenario at hand. We show that though insufficient in an individual capacity, the integration of this trio of features is sufficient to solve the scenario that we present. We test our system with an example problem that involves sof t and hard goals, as well as goal deadlines and action costs, and show that the planner is capable of incorporating sensing actions and execution monitoring in order to produce goal-fulfilling plans that maximize the net benefit accrued.
AB - In this paper, we present an integrated planning and robotic architecture that actively directs an agent engaged in an urban search and rescue (USAR) scenario. We describe three salient features that comprise the planning component of this system, namely (1) the ability to plan in a world open with respect to objects, (2) execution monitoring and replanning abilities, and (3) handling sof t goals, and detail the interaction of these parts in representing and solving the USAR scenario at hand. We show that though insufficient in an individual capacity, the integration of this trio of features is sufficient to solve the scenario that we present. We test our system with an example problem that involves sof t and hard goals, as well as goal deadlines and action costs, and show that the planner is capable of incorporating sensing actions and execution monitoring in order to produce goal-fulfilling plans that maximize the net benefit accrued.
UR - http://www.scopus.com/inward/record.url?scp=77958608843&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77958608843&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:77958608843
SN - 9781577354666
T3 - Proceedings of the National Conference on Artificial Intelligence
SP - 1561
EP - 1566
BT - AAAI-10 / IAAI-10 - Proceedings of the 24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference
PB - AI Access Foundation
Y2 - 11 July 2010 through 15 July 2010
ER -