Planning as search: a quantitative approach
Artificial Intelligence
Cognitive science: an introduction
Cognitive science: an introduction
Artificial Intelligence
Automatically generating abstractions for planning
Artificial Intelligence
Two manipulation planning algorithms
WAFR Proceedings of the workshop on Algorithmic foundations of robotics
An algorithm for probabilistic planning
Artificial Intelligence - Special volume on planning and scheduling
A motivational system for regulating human-robot interaction
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Robot Motion Planning
Using Semantic Networks for Knowledge Representation in an Intelligent Environment
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
mGPT: a probabilistic planner based on heuristic search
Journal of Artificial Intelligence Research
Improving efficiency in mobile robot task planning through world abstraction
IEEE Transactions on Robotics
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In order to reduce tbe number of search space in planning, many abstraction tecbniques are introduced. For example, several hierarchical planners already provide significant reduction in search space. Hierarchical planning in real world, bowever, requires not only planning knowledge such as plan operators but domain knowledge used for describing world model. One of most important issue for Hierarchical Planning through Operator and World Abstraction (HPOWA) is to model an efficient, semantic, and flexible knowledge representation for both planning and domain knowledge. From tbe profound investigation of existing abstraction-based planning researcbes, we obtain several limitations of hierarchical planning for real world environments. Tbus, we apply ontology to model knowledge representation for operator, world model and tbeir interaction. Constructed robot ontology consists of action, object and context classes. Tbe three layers of concepts link up operator knowledge with domain knowledge in world model. Tbe concepts for each class are hierarchically represented for efficient hierarchical reasoning. Tbe semantic relations among tbe domain concepts or sequential relations between plan operators are represented as relations and attributes of the ontology.