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A study and implementation of mapping and speech recognition techniques for an autonomous mobile robot based on ROS

机译:基于ROS的自主移动机器人映射和语音识别技术的研究与实现

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Autonomous mobile robots work in close interaction with humans in environments such as homes, hospitals, public places and disaster areas. In autonomous mobile robots, the main constraints are safety, autonomy and efficiency in helping the humans. Given these constraints, developing the autonomous mobile robot technologies is a major challenge for both the industry and the research society. This paper work is about how an indoor autonomous mobile robot can work based on robot operating system and using Lidar and other sensors to create a map of an environment, and perform autonomous navigation with using capabilities like dynamic obstacle avoidance, speech recognition and video streaming. To achieve the above features, different algorithms like SLAM, AMCL, dynamic window approach algorithms, and CMU PocketSphinx speech recogniser are used. For video steaming, ROS web video server is used and the recorded video can be sent to a remote desktop system using ROS network.
机译:自主移动机器人在家庭,医院,公共场所和灾区等环境中与人类的密切互动。 在自主移动机器人中,主要限制是帮助人类的安全性,自主权和效率。 鉴于这些限制,发展自主移动机器人技术是行业和研究会的主要挑战。 本文的工作是关于室内自主移动机器人如何基于机器人操作系统的工作,并使用LIDAR和其他传感器创建环境的地图,并使用动态障碍避免,语音识别和视频流等功能进行自主导航。 为了实现上述功能,使用不同的算法,如SLAM,AMCL,动态窗口方法算法和CMU PocketSphinX语音识别器。 对于视频蒸,使用ROS Web视频服务器,并且可以使用ROS网络发送录制的视频。

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