Research On Multi Robots Exploration Optimization Based On Artificial Bee Colony Algorithm And Clustering

In recent years,various kinds of disasters and accidents have occurred frequently,and the demand for exploration and rescuing work on site is more urgent.At the same time,the environment in the rescuing site has become harsh and complex,and artificial exploration and rescuing has become a difficult and dangerous work.The rapid development of mobile robot technology brings a new direction to solve this arduous task.The search and rescue of mobile robot for disaster scene is an important research content of robot technology.In this paper,the multi-robot exploration optimization algorithm is studied on two optimization levels,which consist of dividing and assigning.K-means clustering algorithm is an unsupervised algorithm with simple operation.By using the k-means algorithm,the distribution area of the target point is divided,and the workload of each region is ensured.In the designated exploration area,the robot movement will not collide with each other.Considering that the k-means algorithm is sensitive to the initial center,it may be wrong for some outliers.Using the artificial bee colony algorithm to optimize the clustering algorithm and proposed the idea of k-means with non-iteration,meanwhile,the artificial bee colony algorithm is improved to expedite the search speed and boost exploit accuracy of the solution.The optimized k-means algorithm is used to cluster the data in UCI data,and the results show that the proposed algorithm improves the stability of clustering.Assignment problem is a combinatorial optimization problem.The artificial bee colony algorithm is generally used for continuous optimization problems,and different combination problems have different solutions.Therefore,the artificial bee colony algorithm should be improved by means of the search and updating method of the feasible solution.The improved algorithm is tested by two assignment examples,and compared with other methods,the results show that the proposed algorithm is feasible and effective.In the study of the problem,two-objective robot assignment models are established.Therefore,a multi-objective artificial bee colony algorithm is designed to optimize the two-objective problem,and the algorithm runs on the standard test function,confirming the effectiveness of the multi-objective artificial bee colony algorithm.The proposed combination problem coding and updating method is integrated into the multi-objective mechanism,which can be used to solve the problem of robot assignment of two objectives.Finally,the proposed algorithm is used to carry out the real computation,which makes the research scheme of this paper constitute a complete system.Including the k-means clustering division based on the exploration target points and the optimization of the two-objective assignment;Furthermore,the selection method of optimal compromise solution is proposed.