A Robot Task Planner that Merges Symbolic and Geometric Reasoning
نویسندگان
چکیده
We have developed an original planner, aSyMov, that has been specially designed to address intricate robot planning problems where geometric constraints cannot be simply “abstracted” in a way that has no influence on the symbolic plan. This paper presents the ingredients that allowed us to establish an effective link between the representations used by a symbolic task planner and the representations used by a realistic motion and manipulation planning library. The architecture and the main plan search strategies are presented together with an illustrative example solved by a prototype implementation of aSyMov. At each step of the planning process both symbolic and geometric constraints are considered. Besides, the planning process tries to arbitrate between finding a plan with the level of knowledge it has already acquired, or “investing” more in a deeper knowledge of the topology of the different configuration spaces it manipulates.
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