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Towards Integrating Hierarchical Goal Networks and Motion Planners to Support Planning for Human Robot Collaboration in Assembly Cells

AAAI Conferences

Low-level motion planning techniques must be combined with high-level task planning formalisms in order to generate realistic plans that can be carried out by humans and robots. Previous attempts to integrate these two planning formalisms mostly used either Classical Planning or HTN Planning. Recently, we developed Hierarchical Goal Networks (HGNs), a new hierarchical planning formalism that combines the advantages of HTN and Classical planning, while mitigating some of the disadvantages of each individual formalism. In this paper, we describe our ongoing research on designing a planning formalism and algorithm that exploits the unique features of HGNs to better integrate task and motion planning. We also describe how the proposed planning framework can be instantiated to solve assembly planning problems involving human-robot teams.


Assessing the Expressivity of Planning Formalisms through the Comparison to Formal Languages

AAAI Conferences

From a theoretical perspective, judging the expressivity of planning formalisms helps to understand the relationship of different representations and to infer theoretical properties. From a practical point of view, it is important to be able to choose the best formalism for a problem at hand, or to ponder the consequences of introducing new representation features. Most work on the expressivity is based either on compilation approaches, or on the computational complexity of the plan existence problem. Recently, we introduced a new notion of expressivity. It is based on comparing the structural complexity of the set of solutions to a planning problem by interpreting the set as a formal language and classifying it with respect to the Chomsky hierarchy. This is a more direct measure than the plan existence problem and enables also the comparison of formalisms that can not be compiled into each other. While existing work on that last approach focused on different hierarchical problem classes, this paper investigates STRIPS with and without conditional effects; though we also tighten some existing results on hierarchical formalisms. Our second contribution is a discussion on the language-based expressivity measure with respect to the other approaches.


Höller

AAAI Conferences

From a theoretical perspective, judging the expressivity of planning formalisms helps to understand the relationship of different representations and to infer theoretical properties. From a practical point of view, it is important to be able to choose the best formalism for a problem at hand, or to ponder the consequences of introducing new representation features. Most work on the expressivity is based either on compilation approaches, or on the computational complexity of the plan existence problem. Recently, we introduced a new notion of expressivity. It is based on comparing the structural complexity of the set of solutions to a planning problem by interpreting the set as a formal language and classifying it with respect to the Chomsky hierarchy. This is a more direct measure than the plan existence problem and enables also the comparison of formalisms that can not be compiled into each other. While existing work on that last approach focused on different hierarchical problem classes, this paper investigates STRIPS with and without conditional effects; though we also tighten some existing results on hierarchical formalisms. Our second contribution is a discussion on the language-based expressivity measure with respect to the other approaches.


Reducing the Representational Distance Between Application Domain Experts and AI Planning Technology: a compilation approach

AAAI Conferences

actions map to the different levels at which experts reason. When considering a building at the foundations level, an expert Figure 2: Subcomponent Structure Primitive Actions with Abstract and may place the constraint that the foundations must be laid before the drains. This constraint is placed on the abstract LAYaction of class FOUNDATIONS, but it is to be followed by all the actions of the FOUNDATIONS subcomponents. Primitive Actions are only associated with components that do not have subcomponents and they correspond to the actions that will appear in the final construction plan for a building. Primitive actions may be related to components through both the Must and Infer relationship types. Dependency Modelling Like action knowledge, expert knowledge about dependency is organised around components. Figure 3 shows the relationship Under existing between the classes BEAM and DRAIN. The semantics are that an instance of class DRAIN will pass under an instance of class BEAM. Thus, the actions that lay the drain must be completed before work commences on the beam. This relationship can be expressed by placing the temporal ordering constraint Drain.abstract-action