Research on Path Planning and Machine Learning Module in Vision Navigation System of Indoor Mobile Robot

With the growth of social demand and the continuous breakthroughs in the field of unmanned intelligence, mobile robots have gradually entered the public's vision. They have application backgrounds in the fields of daily household, industrial production, unmanned exploration and even national defense. Autonomous navigation, as its core technology, has always been the focus of research in this field. Considering the advantages of visual sensors such as low cost and strong perception ability, this paper studies visual SLAM and path planning with visual navigation as the goal. Machine learning is a branch of artificial intelligence, which deals with the use of computers for learning without explicit programming. This is a process of computer analyzing data and making predictions based on previous experience. In this paper, we will discuss the path planning and machine learning in the vision navigation system of indoor mobile robot. Path planning is an important part of any autonomous system, because it determines how the robot should move to reach its destination or target. In this article, we will discuss path planning using different techniques such as heuristic search.