Grasp learning has become an exciting and important topic in robotics. Just a few years ago, the problem of grasping novel objects from unstructured piles of clutter was considered a serious research challenge. Now, it is a capability that is quickly becoming incorporated into industrial supply chain automation. How did that happen? What is the current state of the art in robotic grasp learning, what are the different methodological approaches, and what machine learning models are used? This review attempts to give an overview of the current state of the art of grasp learning research.
翻译:格拉斯普(Grasp)的学习已成为机器人中令人兴奋和重要的话题。就在几年前,从无结构的杂乱堆中捕捉新物品的问题被认为是一项严重的研究挑战。 现在,这是一个正在迅速融入工业供应链自动化的能力。 是如何发生的? 机器人掌握学习的目前最新水平是什么? 不同的方法是什么? 使用的是什么样的机器学习模式? 本次审查试图概括一下掌握学习研究的当前水平。