Research Of Indoor Relative Positioning Method In Multi-robot System

Multi-robot System(MRS)is one of the research hotspots in the field of robotics today.The system is a collection of multiple robots,through the mutual cooperation between the robots,to complete a complex system of collective tasks.Multi-robot systems have a very wide range of application scenarios,including positioning systems,patrol systems,continuous monitoring systems,and traffic control systems.Among them,indoor positioning is the focus and difficulty of the multi-robot system positioning problem.Compared with the outdoor positioning environment,the indoor environment has many limitations and complexity,such as electromagnetic waves cannot pass through the reinforced concrete building structure and multipath effects,so the accuracy of outdoor positioning technology is far from the user’s requirements.Therefore,the indoor relative positioning problem becomes a key technology.In this paper,an in-depth study is conducted on the indoor positioning method and positioning accuracy of the multi-robot system.The main research contents are as follows:(1)Based on the principle of RSSI ranging signal,a multi-robot system to achieve indoor collaborative positioning is proposed.Compared with the traditional positioning algorithm using fixed anchor nodes,this method is to install distance sensors and signal receivers on three mobile robots in the environment,and use these three robots as positioning "anchor nodes" to transmit and receive through sensors.Using the RSSI ranging algorithm to calculate the distance between the robot and the point to be measured,and then use the multilateral positioning principle to determine the exact position of the point to be measured.The advantage is that in small space environments such as indoors,positioning tasks can be completed without requiring many anchor nodes,reducing communication costs.At the same time,an algorithm is designed to ensure that when multiple robots are patrolling and monitoring in the designated area,if any robot finds a target that meets the characteristics and enters the monitoring range,it uses the communication architecture to perform a global broadcast to control all robots to move to the target.Then use the multilateral ranging algorithm for coordinated positioning to ensure that the multi-robot system from indoor patrol to coordinated positioning can be smoothly and quickly realized.(2)For the problem of noise interference in the indoor positioning process of the multirobot system,which affects the positioning accuracy.An Unscented Kalman Filter(UKF)algorithm based on game theory is proposed to realize the coordinated positioning of multirobot systems.This method uses game theory to screen the relative information conflicts between multiple robots,and conducts coordinated positioning based on the consistency information obtained after screening.At the same time,a co-location formula combining relative information and UKF is derived.The advantage is that the game can effectively eliminate information conflicts between robots,and the UKF algorithm also has better positioning accuracy than the traditional extended Kalman filter(EKF).Finally,it is verified through simulation that the use of game theory not only eliminates the redundancy of perception data between robots during multi-robot coordinated positioning,but also reduces some unnecessary calculations,thereby ensuring that the pose during the coordinated positioning process is more accurate and reliable.