SLAM and Navigation of Indoor Wheeled Robot based on Ros with Intelligent Voice Recognition
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Yuanjia Ma, Shuang Zheng, Jinghui Xu, Marifel Capili Kummer
The complexity and changeability of the working and living spaces have been observed to influence the difficulty of mobile robots to adapt to different indoor environments. When they enter the unknown environment, they become unfamiliar with the environment information and their own location. This observation requires mobile robots to have autonomous navigation capability. This study used Mecanum wheels to ascertain free movement of indoor robots in all directions, especially in the narrow indoor spaces. A hardware platform equipped with lidar and other sensors were developed to meet the challenges of indoor navigation. This enabled the indoor robot to efficiently realize indoor simultaneous localization and mapping, and navigate based on the map independently established by the robot. Additionally, voice interaction and graphical display of upper computer were realized in human-computer interaction.
SLAM; Indoor Navigation; Wheeled Robot; ROS