Abstract
Virtual guide framework allows efficient learning and control of complex robot behaviors in human-robot interaction scenarios. The framework can help to guide users to move in a predefined direction or prevent them to enter a forbidden-region. As such, the framework also allows efficient modulation of regions by changing of parameters. In this paper, we introduce and evaluate the means of adapting path parameters through physical interaction. The main goal was to introduce an algorithm into a virtual guide framework which can partially modify the path trajectories. The path updates are based on physical interaction and allow human intervention to improve the task performance. This enables to update the path trajectory only where needed and hence, to bypass the need to re-learn the whole trajectory from scratch. Since virtual guides are also active while learning, the required effort from the user is lower compared to the required effort when the user is teaching the robot with kinesthetic guidance. The effectiveness of the proposed algorithm has been demonstrated with simulation results and experiments on a KUKA LWR robot.
This work was supported by IJS Director’s found grand CoBoTaT.
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Petrič, T., Žlajpah, L. (2020). On-line Adaption of Virtual Guides Through Physical Interaction. In: Berns, K., Görges, D. (eds) Advances in Service and Industrial Robotics. RAAD 2019. Advances in Intelligent Systems and Computing, vol 980. Springer, Cham. https://doi.org/10.1007/978-3-030-19648-6_34
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