Multi-Level Task Learning Based on Intention and Constraint Inference for Autonomous Robotic Manipulation
Christoph Willibald,Dongheui Lee,Christoph Willibald,Dongheui Lee
To perform tasks in unstructured environments, robots need to be able to apply learned skills to different contexts and to autonomously make decisions online. We, therefore, developed a novel data-driven task learning approach that segments a task demonstration into simpler skills and structures them in a high-level task graph. In contrast to other state-of-the-art methods, the presented approach ...
