| Load-haul-dump is an important equipment for trackless mining in underground mines.It has the advantages of flexibility,mobility and high efficiency.It is widely used in the process of shoveling,loading and transportation of underground ore.In recent years,the technology of intelligent mine has developed rapidly,and the popularization and application of technology has led to the development of intelligent load-haul-dump.Autonomous driving technology is one of the core technologies of intelligent load-hauldump.Therefore,the positioning,mapping,path planning and path tracking control problems faced by load-haul-dump are studied.The main research contents are as follows :(1)Research on mapping and positioning of load-haul-dump.The working environment and autonomous driving requirements of the load-haul-dump are analyzed.The simultaneous localization and mapping(SLAM)algorithm based on laser sensor is used to construct the map for the dark light environment of underground mines.On the basis of the global map,the radio frequency identification technology is used to provide the initial pose for coarse positioning,and the standard normal distribution matching(NDT)algorithm is used to realize the relocation and solve the positioning problem of the load-haul-dump in the long-term work of the underground mine.Finally,the mapping and positioning experiment is carried out in the simulated roadway.The results show that the algorithm can realize the map construction of underground mine and the autonomous positioning of load-haul-dump(2)Research on path planning of load-haul-dump.In the global path planning,a viewable environment map is constructed,and a bidirectional breadth-first search algorithm is used for path search.In the local path planning,the path planning method based on environmental probability is studied.The offline cubic spline path library is generated according to the kinematic constraints of the load-haul-dump,and the path with the maximum probability density is selected as the final execution path.Aiming at the working characteristics of load-haul-dump staying at multiple target points,the algorithm framework of road point navigation is constructed.Finally,the path planning simulation experiment is carried out to verify the feasibility and real-time performance of the algorithm.(3)Research on path tracking control of load-haul-dump.The load-haul-dump is a front and rear articulated structure.In this thesis,the kinematics modeling is carried out according to its structural characteristics,and the kinematic constraints and error definition of the underground scraper are clarified.The path tracking controller of nonlinear model predictive control(NMPC)is designed according to the kinematic model.The effect of NMPC path tracking control is verified in the simulation.The results show that the path tracking controller based on NMPC has better tracking accuracy.(4)Experimental research on autonomous driving system of load-haul-dump.Modified the traditional load-haul-dump,installed the on-board control module,environment sensing module and state sensing module,and completed the deployment of the autonomous driving system.The test of autonomous driving of load-haul-dump was carried out in the factory of the cooperative unit,which proved the overall effectiveness of the unmanned driving scheme.The thesis has 89 diagrams,8 tables,and 87 references. |
