Port AGV Path Planning And Design Of Automatic Fire Sensing System

Automatic Guidance Vehicle(AGV)has the characteristics of automation and high degree of intelligence,and is now widely used in industrialized places such as warehouses,ports and terminals,etc.The main research revolves around how to achieve precise operation of AGVs to obtain high production efficiency while saving costs.This requires AGVs to be able to achieve high precision path planning as well as to reduce some additional costs that may be incurred by the vehicle itself due to safety hazards.Particle swarm optimization algorithm is widely used in optimization research and has achieved good performance in path planning research,but the particle swarm algorithm in the search iteration,easy to fall into the local optimal solution,and the late convergence is slow,which makes the use of particle swarm algorithm for path planning efficiency and accuracy is weakened,how to improve the accuracy of planning results and reduce the cost of operations has become a priority.In this paper,we propose an improved path planning algorithm based on particle swarm algorithm,which improves the global convergence of the search while obtaining a feasible path with shorter path length and less energy consumption;considering some additional cost issues,we introduce an automatic fire extinguishing and temperature sensing system,which can realize the prevention and timely solution of fire safety problems,monitor the fire safety status of the automatic guided vehicle,and guarantee that it can carry out normal production operations.The main work is summarized as follows.(1)An improved particle swarm path planning algorithm based on opposition learning is proposed.In the algorithm,in order to improve the accuracy of the solution of each generation in the iterative process of particle swarm search,the idea of opposition learning is introduced,that is,in the process of iterative search by particles,the opposition value of the currently obtained solution is taken into account,the optimality of the current solution and the opposition solution is judged by the cost function,the best is selected as the initial value of the next iteration,and the cycle is chosen until the end of the iteration;when the particle velocity is updated,an inverse S-shaped function with linear decrement to achieve a balance between the global search and local search ability of the particles in order to improve the accuracy of the algorithm,and dynamically adjust the search step of the particles by adaptive adjustment coefficients and random factors to avoid the emergence of a local optimal solution when the particles perform position updates.Finally,the feasibility and superiority of the algorithm are verified by performing path planning in two different sets of environmental maps.(2)In path planning,algorithm improvements can achieve better performance,but the environment map may also have an impact on the planning results.For the processing of the environmental map,a region division method is proposed,in which the particle swarm algorithm is first used to obtain an initial set of feasible path groups,and combined with the region division method,the environmental map is decomposed into several subregions,and the size of the search area is reduced by searching for paths within the subregions to implement refined search;the particle swarm algorithm is combined with the gravitational search algorithm,while the fractional order calculus is introduced into the hybrid algorithm of velocity update term into the hybrid algorithm,a hybrid path planning algorithm based on map region division is proposed.The method improves the convergence performance of the algorithm with the help of the memory property of fractional order,while the energy consumption constraint is taken into account in the position update term,and the update step is adjusted by dynamic parameters,and a path with lower energy consumption has been obtained.Simulation experiments have verified that the optimal path obtained after area division has good performance in terms of convergence performance,path accuracy and energy consumption,and has good feasibility.(3)In view of the possible safety hazards,especially fire safety hazards,of the port AGV operation,an automatic fire extinguishing system and temperature sensing system are designed to prevent the safety of the AGV’s own equipment and electrical wiring,to solve the fire safety problems that may occur in the AGV,as well as the problems that may be caused by hot weather or other thermal runaway phenomena.The system minimises additional costs in the event of fire safety problems before they are incurred.Finally,the feasibility and practicality of the designed system has been verified by conducting system trials on the port AGV.