The BesMan Learning Platform for Automated Robot Skill Learning
Lisa Gutzeit, Alexander Fabisch, Marc Otto, Jan Hendrik Metzen, Jonas Hansen, Frank Kirchner, Elsa Andrea Kirchner
In Frontiers in Robotics and AI, o.A., volume 5, pages 43, May/2018.
Abstract
:
We describe the BESMAN learning platform which allows learning robotic manipulation behavior.
It is a stand-alone solution which can be combined with different robotic systems and applications.
Behavior that is adaptive to task changes and different target platforms can be learned to solve
unforeseen challenges and tasks, which can occur during deployment of a robot. The learning
platform is composed of components that deal with preprocessing of human demonstrations,
segmenting the demonstrated behavior into basic building blocks, imitation, refinement by means
of reinforcement learning, and generalization to related tasks. The core components are evaluated
in an empirical study with 10 participants with respect to automation level and time requirements.
We show that most of the required steps for transferring skills from humans to robots can be
automated and all steps can be performed in reasonable time allowing to apply the learning
platform on demand.
Files:
main_pre_print.pdf
Links:
https://doi.org/10.3389/frobt.2018.00043