A novel Skill-based Programming Paradigm based on Autonomous Playing and Skill-centric Testing
Simon Hangl, Andreas Mennel, Justus Piater

TL;DR
This paper presents a new robot programming paradigm combining autonomous skill learning through playing and visual programming, making robot programming more accessible for beginners by simplifying task implementation and testing.
Contribution
It introduces an integrated framework that combines autonomous skill acquisition via robotic playing with visual programming and skill-centric testing for easier robot programming.
Findings
Enables unexperienced users to program robots with minimal effort.
Allows continuous testing of skills without detailed component knowledge.
Reduces barriers to robot programming through autonomous learning and visual interfaces.
Abstract
We introduce a novel paradigm for robot pro- gramming with which we aim to make robot programming more accessible for unexperienced users. In order to do so we incorporate two major components in one single framework: autonomous skill acquisition by robotic playing and visual programming. Simple robot program skeletons solving a task for one specific situation, so-called basic behaviours, are provided by the user. The robot then learns how to solve the same task in many different situations by autonomous playing which reduces the barrier for unexperienced robot programmers. Programmers can use a mix of visual programming and kinesthetic teaching in order to provide these simple program skeletons. The robot program can be implemented interactively by programming parts with visual programming and kinesthetic teaching. We further integrate work on experience-based skill-centric robot…
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Taxonomy
TopicsRobot Manipulation and Learning · Reinforcement Learning in Robotics · Teaching and Learning Programming
