Research Of Swarm Robots For Multi-target Search In Unknown Complicated Environments

As a typical distributed group intelligent artificial system,swarm robots system is composed of many individual robots,which has the same simple structure and function.It is inspired by the behavior of social biological swarms in nature.Through the coordinated control of the members,at the same time,taking full advantage of the individual local perception and interaction,the system can emerge learning,cooperation and other intelligent behavior,which can be used to solve practical problems,such as some complex tasks that is difficult or impossible to complete for single robot system or multi-robot system.Aiming at the multi-target searching problem of swarm robots in unknown complex environments,this paper studies the method of coordinated control of the robots.The subject has great practical significance and application value and is beneficial to achieve the target search and rescue,path planning,formation control and cooperation,and navigation,etc.In addition,the research results can be widely used in coal mine rescue,toxic chemical leakage source location,military confrontation,peacekeeping and anti-terrorism and so on.The main work and research results of this paper are as follows:(1)Firstly,this paper considers the problem of self-organization task assignment of swarm robots.And,on the basis of the self-organizing task division model,which is based on target response threshold and probability principle,the text introduces negative feedback adjustment mechanism,including the assessment of member advantages status,withdrawal of the union and the second joined,and then,a simple dynamic closed-loop adjustment selforganization task division method is given.(2)For the coordinated control strategy of the individual robot,the paper designs the individual motion control method based on the SVF-Model(simplified virtual-force model),so that the robot can judge the reasonable movement trend only according to the state and position information of the nearest neighbors.(3)For the coordinated control of the group behavior on the sub-swarm level,the strategy of cooperative search method,among the members of the sub-swarm,based on the EPSO(extended particle swarm optimization)algorithm is adopted.Simultaneously,the text also considers the robot roaming,collision and other underlying behavior planning.For the roaming individuals in the environment,the paper designs a roaming search strategy based on a method that is different from the direction of the movement of the left and right individuals and maximizes the search area.For the collision avoidance planning of the robots,anindividual collision avoidance method is also given on the basis of the SVF-Model.At the same time,aiming at the complex convex and non-convex obstacle in the environment,the barrier-following motion is designed.In this paper,a novel search method based on a simplified virtual-force model is proposed for multi-target search of swarm robotics(SRSMT-SVF),and the algorithm is simulated in the two environments with unknown convex obstacle and dynamic non-convex obstacle.Simulation results show that the system has good performance of flexibility,scalability and efficiency.