Aiming at the navigation problems of traditional mobile robots in multi-target points

two aspects are considered:optimal traversal of multiple target points and obstacle avoidance for mobile robots.A mobile robot based on multi-sensor fusion simultaneous localization and mapping(SLAM)is designed.By integrating real-time appearance-based mapping(RTAB-Map)and Gmapping algorithms

parameters are optimized to construct high-quality maps.Meanwhile

the ant colony optimization(ACO)algorithm is utilized for the optimal traversal of multi-target points.For the traditional A

*

algorithm

a segmented multi-order Bezier curve is proposed to optimize the pat

h trajectory.The feasibility is verified through Python simulation

and maps are constructed to validate the algorithm.The results indicate that the mobile robot can achieve autonomous navigation and mapping

and the feasibility of the design is verified from map quality

path distance

functionality

and path smoothness.The motion efficiency is improved

and both safety and robustness are enhanced.