Indoor mobile robots have been a hot topic in recent years, and synchronous localization and mapping technology is one of the key technologies of mobile robots. For this reason, this paper designs a synchronous localization and mapping system for smart cars based on the Robot Operating System (ROS). With Gmapping as the core algorithm, the odometer constructed by the motor encoder is used to compensate for the motion distortion of each frame of the single-line laser radar. The laser radar data and odometer data after motion distortion compensation are used as the input of the Gmapping algorithm; then, the particles are initialized by the Gmapping algorithm, the proposed distribution considering the observation quantity is constructed and the particles are sampled to estimate the position and posture of the smart car, the particles are resampled with the resampling importance coefficient and the resampling threshold is set, and the map state of each particle is updated using a binary Bayesian filter; finally, the position estimation and map data of the smart car are output based on the Gmapping algorithm. The experimental results show that the designed synchronous localization and mapping system can accurately estimate the position and posture of the smart car and construct the map in a small-scale environment, meeting the design goal requirements.
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