Robot autonomous navigation system based on improved Gmapping algorithm and optical sensing techniques

To realize the autonomous navigation of mobile robots, this study built a new robot autonomous navigation system by improving the Gmapping algorithm. The new system uses the Gmapping algorithm to realize the robot's mobile position positioning process and map information construction, and then uses the genetic algorithm to improve the map positioning optimization effect of the Gmapping algorithm, and uses optical sensors to improve accuracy for map building and robot localisation. In addition, the new method integrates a high-resolution optical camera to improve the accuracy of the navigation system through V-SLAM (Visual SLAM) technology. The research outcomes indicate that the improved Gmapping algorithm has a better navigation map construction effect in the comparison of different data sets. Among them, the number of effective particles of the improved Gmapping algorithm can reach up to 33, which is 19 higher than that of other algorithms. Meanwhile, the number of effective particles of the improved Gmapping algorithm in different data sets is the largest. In the comparison of navigation accuracy of different algorithms, the navigation accuracy of the improved Gmapping algorithm can reach up to 96.3%. In the BotanicGarden Dataset, the navigation accuracy can reach 95.4%, which is 28.0% higher than that of other algorithm models. It can be seen that the robot autonomous navigation system built in the study can realize robot autonomous navigation and has a good navigation effect. Optical sensors effectively improve the accuracy and robustness of robot navigation systems. The study has a good guiding role in the research of robot autonomous navigation.