Extending Graphplan to handle uncertainty and sensing actions
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Interleaving Planning and Robot Execution for Asynchronous User Requests
Autonomous Robots - Special issue on autonomous agents
Experiences with an Autonomous Robot Attending AAAI
IEEE Intelligent Systems
Deriving and Using Abstract Representation in Behavior-Based Systems
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Weak, strong, and strong cyclic planning via symbolic model checking
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
Bridging the gap between planning and scheduling
The Knowledge Engineering Review
2003 AAAI robot competition and exhibition
AI Magazine
Sapa: a multi-objective metric temporal planner
Journal of Artificial Intelligence Research
The metric-FF planning system: translating "Ignoring delete lists" to numeric state variables
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
Reactive planning in a motivated behavioral architecture
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Autonomous planning for mobile manipulation services based on multi-level robot skills
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Dynagent: an incremental forward-chaining HTN planning agent in dynamic domains
DALT'05 Proceedings of the Third international conference on Declarative Agent Languages and Technologies
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The AAAI Mobile Robot Challenge requires robots to start from the entrance of the conference site, find their own way to the registration desk, socially interact with people and perform volunteer duties as required, then report at a prescribed time in a conference hall to give a talk and answer questions These specifications convey some interesting planning problems that appear to be too complex for some of the most efficient AI planning systems that we analyzed Based on this analysis, we present a new planning approach that we are developing to meet the challenge Preliminary results show that our approach performs much better on robot conference planning problems than any of the other AI planning systems we tested.