| With the rapid development and progress of multi-robot cooperative motion technology,multi-robot can replace human beings to achieve more complicated operations in special scenarios.As a typical scenario,the application of Automated Guided Vehicle(AGV)has greatly reduced human burden,and it plays an important role in material handling,special area detection,and so forth.There are diverse commonly used AGV guidance methods,including electromagnetic induction,laser induction,and Radio Frequency Identification(RFID).In addition,traditional AGV robots need to be customized according to actual application scenarios in most cases,exhibiting advantages like high efficiency and good adaptability.However,there are some issues that the manufacturer cannot produce such robots because the production line does not meet some conditions.The multi-robot cooperative motion technology can reduce the emergence of scene customization,and realize autonomous obstacle avoidance and navigation.At the same time,it will also reduce the cost of traditional guidance mode and has strong flexibility.This is of great significance for actual production.According to actual needs of production and life,this thesis proposes a cooperative obstacle avoidance control strategy for multi-robot.Specially,the real-time distributed algorithm is used to realize the cooperative obstacle avoidance in multi-robot dynamic scenarios.The main work of this thesis is as follows:(1)Aiming at the issue of complexity and real-time operation of the multi-robot cooperative movement environments,this thesis utilizes the Model Predictive Control(MPC)combined with mathematical programming,proposes a multi-robot cooperative movement algorithm with real-time planning and distributed characteristics,which drives the robot to move towards the target point.This technique can respond quickly and avoid obstacles quickly according to the real-time characteristics of environments.At the same time,the distributed mode can reduce the dependence of the whole system on a single centralized controller and ensure that the multi-robot can plan the path more reasonably during the coordinated movement.(2)According to different requirements of multi-robot application scenarios,combines multiple applications of multi-robots in unknown environments and material handling,this thesis proposes a multi-robot formation priority or speed priority algorithm.As a result,when multi-robots are utilized for environment detection,it is possible to maintain the initial formation as much as possible,formation first algorithm can be used to achieve the detection range and improve the accuracy of environmental information at the same time.In addition,when multi-robots are used for rescue materials,the priority of transportation efficiency is higher than that of maintaining the initial formation.Thus,speed first algorithm can be used to achieve rapid mobility and improve the efficiency of material transportation.Based on the application in various scenarios,the multi-robot cooperative control becomes more intelligent.(3)According to the characteristics of dynamic environments in real scenarios,this thesis utilizes the real-time distributed algorithm,realizes the cooperative obstacle avoidance of two robots in dynamic environment rapidly and efficiently,and ensures that multiple robots can avoid obstacles while making the smallest changes in formation at the same time.Meanwhile,the cooperative control of multi robots is studied,analyzed,and discussed.In detail,when multi robots pass through an intersection at the same time,the proposed algorithm in this thesis can avoid collision,and other situations,and all the multi robots can quickly reach target point through the intersection. |
