Visual Navigation in Real-World Indoor Environments Using End-to-End Deep Reinforcement Learning
IEEE Robotics and Automation Letters(2021)
摘要
Visual navigation is essential for many applications in robotics, from manipulation, through mobile robotics to automated driving. Deep reinforcement learning (DRL) provides an elegant map-free approach integrating image processing, localization, and planning in one module, which can be trained and therefore optimized for a given environment. However, to date, DRL-based visual navigation was valid...
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关键词
Navigation,Robots,Training,Task analysis,Visualization,Reinforcement learning,Cameras
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