论文标题
使用机器学习的移动机器人导航的运动计划和控制：调查
Motion Planning and Control for Mobile Robot Navigation Using Machine Learning: a Survey
论文作者
论文摘要
在复杂的环境中移动是智能移动机器人的重要功能。数十年的研究和工程专门致力于开发复杂的导航系统，以将移动机器人从一个点转移到另一个。尽管他们的整体成功，但最近的新兴研究推力致力于开发机器学习技术以解决相同的问题，这在很大程度上基于深度学习的成功。但是，迄今为止，经典和新兴范式与此问题之间的直接比较并没有太多直接的比较。在本文中，我们调查了在经典导航系统中，将机器学习应用于移动机器人导航中的运动计划和控制的最新作品。被调查的作品分为不同的类别，这些类别描述了学习方法与经典方法的关系。基于此分类，我们确定了共同的挑战和有希望的未来方向。
Moving in complex environments is an essential capability of intelligent mobile robots. Decades of research and engineering have been dedicated to developing sophisticated navigation systems to move mobile robots from one point to another. Despite their overall success, a recently emerging research thrust is devoted to developing machine learning techniques to address the same problem, based in large part on the success of deep learning. However, to date, there has not been much direct comparison between the classical and emerging paradigms to this problem. In this article, we survey recent works that apply machine learning for motion planning and control in mobile robot navigation, within the context of classical navigation systems. The surveyed works are classified into different categories, which delineate the relationship of the learning approaches to classical methods. Based on this classification, we identify common challenges and promising future directions.
