In recent years, the usage of robotic systems has increased significantly in all fields, and there is an increasing focus on developing intelligent systems capable of autonomously navigating in various scenarios. The ROS framework offers multiple solutions to the key SLAM problem in autonomous navigation research. There are still a few challenges to autonomous navigation in indoor environments, such as the lack of reliable Global Positioning System (GPS) data or the need to install WiFi tags or QR code markers. A potential solution is to use 3D BIM models of facilities to aid the localization part of autonomous navigation algorithms by using the semantic information of the static structures like walls and floors of the building. Most modern buildings have a digital twin available, which accurately describes the static physical structure of the building. By feeding these digital models to robotic systems, remotely operated mapping and navigation can be achieved
efficiently. In this research work, a basic BIM-based autonomous navigation framework will be designed to simulate the navigation of a quadruped robot in the Gazebo simulator. Then this framework will be implemented on a Unitree Go1 quadruped robot to verify the real world performance..
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In recent years, the usage of robotic systems has increased significantly in all fields, and there is an increasing focus on developing intelligent systems capable of autonomously navigating in various scenarios. The ROS framework offers multiple solutions to the key SLAM problem in autonomous navigation research. There are still a few challenges to autonomous navigation in indoor environments, such as the lack of reliable Global Positioning System (GPS) data or the need to install WiFi tags or...
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