Autonomous navigation and path planning for mobile robots based on SLAM.

A machine that automatically completes tasks is called an intelligent mobile robot. It can be controlled by a person, can carry out pre-programmed tasks, and can follow a set of rules based on artificial intelligence technology. Its job is to support or take the place of human labor in hazardous or production-related jobs. Mobile robots play a significant role in today's society, such as AGV(Automated Guided Vehicle) trolleys in laboratories and material handling robots in logistics warehouses. SLAM is an acronym for Simultaneous Localization and Mapping, which is mostly used to address the issue of locating a mobile robot while it is operating in an unfamiliar environment and creating a map of that environment. The realization of autonomous navigation is an important direction for the intelligent development of mobile robots, and SLAM technology is the key to the autonomous navigation technology of mobile robots. Combining these two technologies can significantly advance mobile robotics. This thesis focuses on the classification of SLAM technology using different transducers and the principle of related algorithms, analyses some of the problems existing in this technology at this stage and predicts the future development trend, which can provide technical and methodological references for the mobile robot development manufacturers. [ABSTRACT FROM AUTHOR]