A Traceability Algorithm And Experimental Of Air Pollution Source Localization Using Multi-UAV Based On Emotional Quantity

The continuous advancement of the industrialization process has brought huge economic wealth to the country and society,but at the same time,the exposed air pollution problems have become more and more obvious.It is of great significance to formulate an accurate and efficient traceability plan for atmospheric pollutants,and implement targeted treatment at the source of pollutants in a timely manner to effectively avoid or reduce the atmospheric pollution caused by stealth and leakage in chemical industrial parks.Taking the UAV as the airborne platform,this paper proposes and designs a traceability algorithm for air pollutants suitable for multiple UAVs.The effectiveness of the traceability algorithm proposed in this paper is verified through simulation analysis and indoor traceability experiments.The main work of this paper is divided into the following aspects:(1)Construction of background concentration fields for the diffusion of atmospheric pollutants.On the basis of comparative analysis of common gas diffusion models,based on Matlab,Fluent and UE4 software,the background concentration fields of atmospheric pollutant diffusion under two-dimensional ideal conditions,twodimensional turbulent conditions and three-dimensional environmental conditions were established respectively for subsequent use.The simulation experiment verification of the anxiety-auction air pollutant traceability algorithm proposed in this paper.(2)Research and design of air pollutant traceability algorithm based on anxietyauction.Starting from the multi-robot traceability strategy,aiming at the problems and deficiencies in the selection of auction timing in the traditional auction algorithm,the concept of anxiety in psychology is innovatively introduced into the traditional auction algorithm,and an air pollutant traceability algorithm based on anxiety-auction is designed and proposed.The algorithm enables each drone to "rationally" choose the auction time according to its own emotional level,thus avoiding the waste of team resources and effectively improving the overall traceability efficiency.(3)Simulation experiment and result analysis of air pollutant traceability algorithm.The simulation experiment was carried out on the anxiety-auction-based air pollutant tracing algorithm proposed in this paper,and the comparison and analysis were carried out with the traditional auction algorithm based on different environmental factors and conditions,the number of drones,etc.The auction air pollutant traceability algorithm is superior to the traditional auction algorithm in terms of success rate and distance ratio.(4)Construction and experimental design of multi-UAV indoor traceability platform.An atmospheric pollutant traceability platform consisting of UWB indoor positioning device,UAV platform and traceability monitoring and control module was built.Finally,an indoor air pollutant traceability experiment based on multiple UAVs was successfully designed and carried out,which verified this paper.The proposed anxiety-feasibility of the auction algorithm.