Research On Integrated Navigation Method Of Logistics Robot Based On DM Landmark And Lidar

With the rapid development of science and technology and artificial intelligence,the mobile robot is an intelligent product,which can help human reduce labor.It has been applied in various fields,especially in the field of logistics applications.In the modern logistics environment,the mobile robot has become an indispensable logistics tool,but the logistics robot technology under the background of warehousing also faces many problems,especially in robot navigation precision and reliability problems become the difficulty of robot application.Thus the robot technology in-depth study has essential significance and value.Firstly,research on the robot integrated navigation system,introduced the research background and significance of the robot integrated navigation,conducted an in-depth discussion on the research status and key technologies of the robot navigation method,and proposed a logistics based on the integration of Data Matrix(DM)landmarks and lidar Robot integrated navigation solution.Secondly,the traditional Monte Carlo Localization(MCL)algorithm has low Localization accuracy and cannot solve robot abduction.Therefore,the Data Matrix-Monte Carlo Localization(DM-MCL)Localization algorithm is proposed.Firstly,the odometer motion model was established to predict the position of particles,and then the DM landmark data was used to modify its parameters.Then,the DM landmark observation model was established to update the importance weight of particles.Finally,random particles are added according to the camera observation likelihood in the particle resampling process to obtain more accurate particle distribution.Through the simulation experiment of the DM-MCL algorithm,the algorithm can effectively improve the positioning accuracy,solve the robot hijacking problem,and verify the accuracy and effectiveness of the algorithm.Thirdly,the Artificial Bee Colony(ABC)algorithm has the problem of slow optimization speed and easy to fall into the local optimal,and an Ion motion-artificial Bee Colony(IM-ABC)algorithm was proposed.In the early stage of the algorithm,population evolution is guided by the cross-search of cation and ions,which can improve population development.In order to avoid local optimization caused by premature convergence in the early stage,the leading bees use random search to find nectaries,and the following bees use reverse roulette to select nectaries,which can expand the diversity of the population.Flower concentration was introduced into the global updating mechanism to improve the sampling method.Based on these methods,we proposed the improved artificial bee colony algorithm.Finally,the integrated navigation scheme in this thesis is realized on the Robot KIKI-3,which is independently developed and based on the Robot Operating System(ROS).Through the comparative experiments of different navigation methods and multi-obstacle environments,the experiment can prove the accuracy and reliability of the integrated navigation scheme of logistics robots based on the fusion of DM landmarks and lidar.