Research and Application Analysis of Global Path Planning Method Based on Radar and Vision in Robot SLAM

In recent years, the production scale of robots has become larger and larger, involving all aspects of society. Many industries are beginning to introduce robots and use them to better development and production. At the same time, autonomous driving is also a promising research direction, which is expected to reach 8 million autonomous vehicles by 2030, and the passenger car market will account for about 13% of total passenger miles. Autonomous driving will also bring many benefits to people, such as freeing up an average of 50 minutes of extra time for drivers per day, which can reduce accidents by more than 90%. Whether it is a robot or a self-driving car, the most important and critical goal is to ensure that the target task can be completed safely and quickly. Simultaneous localization and mapping (SLAM) technology can better help robots achieve this goal. In this paper, laser SLAM, visual SLAM and laser-visual SLAM algorithms are introduced, and then some related applications are shown. Finally, the future development prospect of SLAM should pay more attention to multi-sensor fusion algorithm.