تقرير
Where To Start? Transferring Simple Skills to Complex Environments
العنوان: | Where To Start? Transferring Simple Skills to Complex Environments |
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المؤلفون: | Vosylius, Vitalis, Johns, Edward |
سنة النشر: | 2022 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Robotics, Computer Science - Machine Learning |
الوصف: | Robot learning provides a number of ways to teach robots simple skills, such as grasping. However, these skills are usually trained in open, clutter-free environments, and therefore would likely cause undesirable collisions in more complex, cluttered environments. In this work, we introduce an affordance model based on a graph representation of an environment, which is optimised during deployment to find suitable robot configurations to start a skill from, such that the skill can be executed without any collisions. We demonstrate that our method can generalise a priori acquired skills to previously unseen cluttered and constrained environments, in simulation and in the real world, for both a grasping and a placing task. Comment: Accepted at CoRL 2022. Videos are available on our project webpage at https://www.robot-learning.uk/where-to-start |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2212.06111 |
رقم الأكسشن: | edsarx.2212.06111 |
قاعدة البيانات: | arXiv |
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