Mobile Obstacle Avoidance And Path Planning Of Intelligent Home Robot

With the continuous development of society,people's demand for quality of life is getting higher and higher.It has become a trend that high-tech enters the family to improve people's quality of life.At present,China's aging problem is becoming more and more serious.In the near future,home robots will play an increasingly important role in caring for the elderly.In the future,home robots can not only provide simple work such as sweeping the floor and washing dishes,but also provide entertainment,security and other services for families.However,in order to provide these services,path planning and obstacle avoidance are essential technical foundations for home robots,which are also the key issues to be solved in this paper.In this paper,the following research work is carried out for the mobile obstacle avoidance and path planning of home robots:1.This paper describes the background and significance of this study,introduces the current domestic and foreign home robot path planning technology,positioning,obstacle detection commonly used technical means and what technical difficulties still exist,and puts forward the content of this study.2.According to the sweeping robot,the mechanical structure of the home service robot is designed,the hardware circuit is designed and the sensor is selected.The upper computer is designed for image acquisition,path planning,sensor data display and so on.The motion model and control mode of the robot are given.3.Obstacle detection is the premise of robot path planning.This paper combines infrared ranging sensor with monocular vision to detect obstacles,expanding the measurement range of obstacles.Monocular vision is used to detect obstacles using HSI obstacle edge detection algorithm which is insensitive to environmental light.Experiments on edge extraction under different illumination environments verify the effectiveness of the selected algorithm.4.Aiming at the slow matching speed of feature points in global positioning of monocular vision,this paper combines monocular vision with inertial sensor positioning.Monocular vision localization is mainly based on feature extraction and feature matching of the image to calculate the position and pose of the robot.Therefore,this paper carries out feature point extraction experiments and feature point matching experiments.In order to verify the effectiveness of the proposed algorithm,localization experiments are carried out in this paper.5.Aiming at the characteristics that obstacles in family environment often change,this paper combines local path planning with global path planning.The improved ant colony algorithm is used for global path planning,and the artificial potential field method is used for local path planning.For the obstacles that do not appear in the global map,but in the path of global path planning,artificial potential field method is used to avoid obstacles within a certain range of robots to cope with the changes of obstacles in the family environment.