Skill parametrization approaches and skill architecture for human-robot interaction

Abstract

There is an ongoing shift in industries from mass production to low-batch-production with highly individualized goods. This increases the programming effort required for the producing machines and robots, which is currently carried out by robot experts. For keeping the production economical, new programming approaches are required, allowing shop-floor workers to instruct robots. One approach is to develop robotic skills, which are pre-programmed software modules that only need to be parametrized by the shop-floor user. In this paper, a new software architecture for robot skills is presented, which aims at robustness and human-robot interaction. In addition, four basic demands on the skill parametrization are described that fasten up the process and increase intuitiveness for the user. We give several examples and implement a screwing skill and a pick & place skill, which are demonstrated in two case studies.