The Improvement Of Artificial Bee Colony Algorithm And Its Application In Robot Path Planning

In recent years,with the rapid development of the fast-moving consumer goods.industry and the application of smart logistics,the mobile robot industry has been booming.According to incomplete statistics,as of 2018,there were more than 1.2 million domestic companies producing mobile robots.The extensive application of robots in various neighborhoods has made the path planning of robots a hot topic of research.In the internet environment,machine intelligence,swarm intelligence and so on complement each other,forming a swarm intelligence space where multiple parties merge.Among them,the research of swarm intelligence not only promotes the development of artificial intelligence,but also provides driving force for application innovation and value creation of the entire science and technology society.At present,the robot path planning problem based on swarm intelligence still has problems such as being greatly affected by environmental models and accuracy,and avoiding obstacles.Artificial bee colony algorithm is an optimization algorithm developed in the field of swarm intelligence in recent years to mimic the behavior of bees collecting honey.It is simple to operate and easy to implement.It has a few control parameters and good search characteristics.Artificial bee colony algorithm has demonstrated its efficiency and practicability in practical applications.Firstly,this paper studies the current development status of artificial bee colony algorithms at home and abroad,analyzes the principles and characteristics of artificial bee colony algorithm,and summarizes the shortcomings and possible development directions.Secondly,Combining the idea of clustering algorithm and the dynamic step size in neighborhood search,this paper proposes an improved artificial bee colony algorithm(KD-ABC)based on K-MEANS algorithm and neighborhood dynamic search,and then validates KD-ABC's effectiveness through experimental.Finally,the KD-ABC algorithm is applied in the research of robot path planning.By modeling the physical space environment,this paper uses the KD-ABC algorithm to plan the optimal path,which verifies the feasibility of the improved algorithm to a certain extent.