In order to solve the problems of indoor mobile robot mapping, such as not detecting small obstacles or unsatisfactory mapping results, this paper proposes a depth camera and LiDAR fusion method for indoor mobile robot mapping. First, the LIDAR odometer was estimated using LIDAR distance scanning. Then the LIDAR odometer, wheeled odometer, and IMU are fused using Kalman filtering to improve the odometer accuracy. Next, the depth image is converted to pseudo-laser information, and the pseudo-laser information and laser information are simply spliced, weighted average and other operations are performed to fuse them into laser information with more comprehensive information. Finally, the mapping algorithm is used to receive the fused laser information and the fused odometer to complete the 2D construction of the surrounding environment. The Gazebo simulation environment and the robot model are built through the ROS2 system for verification. The research results show that the optimized fusion algorithm makes the indoor mobile robot clearer in the mapping of hollow-out objects, more accurate in obstacle, and more accurate in robot. This provides a certain reference for mobile robot map.
For roof and indoor and outdoor waterproof material coating operations, most companies still rely mainly on manual operations, including painting, rolling, manual spraying, and coil covering. There are phenomena such as low construction efficiency and uneven thickness control. In order to improve the construction process and better promote the application of spraying quick-setting products, this design has developed a robot spraying equipment with high accuracy, fast construction speed and convenient construction. Firstly, according to the area covered and the size of the obstacle, the robot's program will partition the whole area and determine the reciprocating working path. Secondly, design the mechanical structure scheme and clarify the technical route. A rotatable four-wheel mobile chassis is used to build workbenches and spray systems. Finally, this paper proposes a method of combining differential GPS and unit decomposition, combining the small area decomposed with high-precision differential GPS navigation and positioning, and designing a path planning algorithm.
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