| Intelligent mobile robot is a kind of robot system which is capable of accomplishing given tasks by autonomous movement of the goals. In this process, it can sense current state and its own environment by carrying the sensor in order to avoid obstacles and complete autonomous navigation. In recent years, with the development of intelligent mobile robot technology and intelligence development, mobile robot is applied in many aspects of human being’s life, including agriculture, industry, service, military technology and scientific exploration and it plays a more and more significant role. It makes more intelligent mobile robot possible based on machine learning, artificial intelligence theory development to mature and sensor’s performance improvement.The main research direction of mobile robot is discussed in detail in this paper, extending existing robot platform and proposing mobile robot’s autonomous obstacle avoidance method based on BP neural network and distance information. Then it proposes mobile robot autonomous movement and learning model. Finally, it conducts a series of experiments aiming at autonomous obstacle avoidance and autonomous movement. Principally work of this article is as follows:Simple to understand the research status and application fields home and abroad and deep to understand the main research direction of intelligent mobile robot, laying the theoretical foundation of proposing the model.This paper comprehensively studies AS_RF mobile robot platform and deeply understands its performance parameters and architecture, systematically studying programming environment given by robot platform and relevant API. Based on mobile robot automatous movement requirement, it extends the sensor system of robot platform, understanding the performance of each sensor, learning data acquisition sensors and getting familiar with the entire robot system hardware and software environment, which, lays the foundation for subsequent work.It represents positional relationship model between robot and obstacle, analyzing the possibility of how to avoid obstacle by using distance data. With precious study and BP neural network, automatous obstacle avoidance method is derived based on BP neural network and distance information. A series of experiments are presented in this paper.On the basis of mobile robots autonomous obstacle avoidance, it proposes autonomous mobile robot learning model combined with GPS, electronic compass, endowing the robot with an initial capacity of voluntary movement in outdoor environment and conducting related experiments. Finally, it analyses experiment result, pros and cons of this model, providing suggestions of future improvements. |
