Over the last several years, use cases for robotics based solutions have diversified from factory floors to domestic applications. In parallel, Deep Learning approaches are replacing traditional techniques in Computer Vision, Natural Language Processing, Speech processing, etc. and are delivering robust results. Our goal is to survey a number of research internship projects in the broad area of 'Deep Learning as applied to Robotics' and present a concise view for the benefit of aspiring student interns. In this paper, we survey the research work done by Robotic Institute Summer Scholars (RISS), CMU. We particularly focus on papers that use deep learning to solve core robotic problems and also robotic solutions. We trust this would be useful particularly for internship aspirants for the Robotics Institute, CMU
翻译:过去几年来,机器人解决方案的使用案例从工厂楼层到国内应用,从工厂楼层到国内应用,多种多样。与此同时,深学习方法正在取代计算机愿景、自然语言处理、语音处理等传统技术,并正在产生积极的成果。我们的目标是调查“对机器人应用的深入学习”这一广泛领域的一些研究实习项目,并为有志学生实习生提供简要的视角。我们在本文件中调查机器人研究所夏季学者(RISS)的研究工作。我们特别侧重于利用深学习解决核心机器人问题和机器人解决方案的文件。我们相信,这对于作为机器人研究所(CMU)的实习者尤其有用。