Artificial Intelligence


High-Level Task Planning in Robotics with Symbolic Model Checking

Authors: Frank Schröder

A robot control system contains a lowlevel motion planner and a high level task planner. The motions are generated with keyframe to keyframe planning while the the tasks are described with primitive action-names. A good starting point to formalize task planning is a mindmap which is created manually for a motion capture recording. It contains the basic actions in natural language and is the blueprint for a formal ontology. The mocap annotations are extended by features into a dataset, which is used for training a neural network. The resulting modal is a qualitative physics engine, which predicts future states of the system.

Comments: 28 Pages.

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Submission history

[v1] 2018-08-11 02:45:16

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