| The development of synchronous positioning and map construction technology has become more and more mature,and it is widely used in various fields such as drones,unmanned vehicles,outer space exploration,disaster relief and rescue,and household service robots.Among them,the exploration of mobile robots for unknown environments has always been one of the research hotspots in this field,but with the increasing market demand and working environment,the working pressure of single robots is increasing,and the research on collaborative exploration of mobile robots is of great significance.In this thesis,a system scheme for the collaborative exploration environment of mobile robots is designed for the unknown indoor environment,and the relevant technical principles involved in it are thoroughly studied to complete the design and implementation of each module of the system.In the initial stage of the task,the overall analysis of the system requirements of the work task and the working principle of each link in the system is introduced,and the hardware and software resources required for the implementation of the system are introduced.The mobile robots and related sensor devices used in the project are modeled,and finally the overall system framework for collaborative exploration of mobile robots in unknown environments is given based on the ROS platform.Aiming at the synchronous positioning and map construction of single robot,the relevant SLAM algorithm of mobile robot is deeply studied,and after analyzing and comparing the common map expression methods,the occupation grid map is selected as the expression method of the environment map,and the construction principle of the occupied grid map is described in detail,and finally the simulation effect of the algorithm mapping is displayed.In the problem of single-robot autonomous exploration,the improved algorithm based on Frontier Exploration is used to solve the boundary target point of the unknown area according to the explored area,and the~*algorithm is used to plan the optimal path for the mobile robot to the target point position,and then combined with the DWA dynamic window method to add dynamic obstacle avoidance function for the mobile robot to improve the robot’s environmental adaptability,and finally convert the mobile robot path information into the mobile robot control information to achieve point-to-point displacement.In the global map fusion link,a centralized system network architecture is built according to the information interaction requirements of mobile robots.Then,the ORB algorithm is used to extract the feature points in the map and describe them,and the Hamming distance is first used for rough matching when matching features,and then the PROSAC algorithm based on the improved RANSAC algorithm is used to eliminate the false matching point pairs in the coarse matching,and finally the global map fusion is completed by the calculated transformation matrix.Finally,the simulated environment and the real indoor environment were built separately.Experiments were carried out on single-robot autonomous exploration and mobile robot collaborative exploration,and the feasibility of the mobile robot collaborative exploration system in unknown environment was verified. |
