Obstacle Avoidance Strategy For Path Planning In Dynamic Unknown Environment

With the continuous improvement of the intelligence of mobile robots,more and more unmanned devices in life have been more widely used.The research of mobile robot related technology has always been the focus of the country's cutting-edge technology research,and it is also an important sign that reflects a country's high-end manufacturing level.It has important strategic significance for the development of mobile robot technology.Path planning technology is a key research content in the field of robot science.How to make mobile robots have a more accurate and keen perception of the surrounding environment information in a dynamic unknown environment,so as to achieve accurate and effective obstacle avoidance is a key issue in research.In order to improve the accuracy of the mobile robot's detection of environmental information in a dynamic and complex environment,an in-depth analysis of the multi-sensor information fusion algorithm is carried out,and the fusion algorithm is improved by combining the artificial potential field method and the rapidly expanding random tree algorithm.Obstacle avoidance ability.The capture of environmental information by mobile robots is mainly based on the real-time detection of surrounding environment information by sensors.In complex and dynamic working environments,individual sensors cannot accurately obtain obstacles.Multi-sensor information fusion technology enables mobile robots to use multiple sensors to group the environment It is possible to fully detect the information.This article discusses the common multi-sensor information fusion algorithms for the problems of low efficiency of multi-sensor information utilization and inaccurate detection,deconstructs the theoretical basis and fusion principle in the process of information fusion,and studies the weighted average information fusion algorithm in detail to improve mobile The efficiency of the robot's use of multi-sensor information.Aiming at the problem of mobile robot path planning algorithm,the artificial potential field method used in this design is studied in detail,and the corresponding improvement strategy is proposed based on the problems revealed in the previous research.Aiming at the problem of target unreachability,an improved mathematical model of repulsive potential field correction is designed to avoid that the mobile robot cannot reach the final target point;innovatively introduces a fast expansion random tree algorithm based on sampling to expand the detection of static environment on the prior map Information,pre-select several temporary target points to avoid mobile robots falling into a local minimum area when using the artificial potential field method and performing dynamic path planning in a dynamic obstacle environment.An obstacle avoidance strategy improves the applicability of path planning algorithms.