Drones have gradually been employed to search for unknown sources during leakage accidents.However,current studies have mainly focused on the single-source search problem,while in practical situations,the location and...Drones have gradually been employed to search for unknown sources during leakage accidents.However,current studies have mainly focused on the single-source search problem,while in practical situations,the location and quantity of the sources are commonly unknown.Existing multi-source search methods fail to accurately estimate the source term,primarily due to the inefficient utilization of concentration information.This limitation results in sub-optimal drone movement strategies.To address these issues,we propose a Dynamic Likelihood-Weighted Cooperative Infotaxis(DLW-CI)approach.The approach integrates the Infotaxis cognitive search strategy with multi-drone cooperation by optimizing both source term estimation and the cooperative mechanism.Specifically,we devise a novel source term estimation method that leverages multiple parallel particle filters,with each filter estimating the parameters of a potentially unknown source in scenarios.Subsequently,we introduce a cooperative mechanism based on dynamic likelihood weight to prevent multiple drones from concurrently estimating and searching for the same source.The results show that the success rate for the localization of 2-4 diffusion sources reaches 90%,78%,and 42% respectively when employing the DLW-CI approach,achieving a 37%average improvement over baseline methods.Our findings indicate that the proposed DLW-CI approach significantly improves estimation accuracy and search efficiency for multi-drone cooperative multi-source search,making a valuable contribution to environmental safety monitoring applications.展开更多
During the scenarios of cooperative tasks performed by a single truck and multiple drones,the route plan is prone to failure due to the unpredictable scenario change.In this situation,it is significant to replan the r...During the scenarios of cooperative tasks performed by a single truck and multiple drones,the route plan is prone to failure due to the unpredictable scenario change.In this situation,it is significant to replan the rendezvous route of the truck and drones as soon as possible,to ensure that all drones in flight can return to the truck before running out of energy.This paper addresses the problem of rendezvous route planning of truck and multi-drone.Due to the available time window constraints of drones,which limit not only the rendezvous time of the truck and drones but also the available period of each drone,there are obvious local optimum phenomena in the investigated problem,so it is difficult to find a feasible solution.A two-echelon heuristic algorithm is proposed.In the algorithm,the strategy jumping out of the local optimum and the heuristic generating the initial solution are introduced,to improve the probability and speed of obtaining a feasible solution for the rendezvous route.Simulation results show that the feasible solution of the truck-drones rendezvous route can be obtained with 88%probability in an average of 77 iterations for the scenario involving up to 25 drones.The influence of algorithm options on planning results is also analyzed.展开更多
针对低空经济发展涉及的安全管理问题,在总结低空经济相关技术路线原理及落地方案的运行经验,分析低空安防普适性的4个建设方案:雷达与通感一体技术融合方案、广播式自动相关监视技术方案、远程识别技术方案和基于TDOA(time difference ...针对低空经济发展涉及的安全管理问题,在总结低空经济相关技术路线原理及落地方案的运行经验,分析低空安防普适性的4个建设方案:雷达与通感一体技术融合方案、广播式自动相关监视技术方案、远程识别技术方案和基于TDOA(time difference of arrival)无线电技术的多源融合方案的基础上,构建无人飞行器探测技术评价指标体系,并建立了一种基于决策试验评估实验室(decision-making trial and evaluation laboratory, DEMATEL)和优劣解距离法(technique for order preference by similarity to an ideal solution, TOPSIS)的多属性评价方法。结果发现,以TDOA为基础的多源融合方案是构建城市低空安防体系的有效路径和普适性方案。研究表明,低空安防体系的建设是一个系统性工程,需要政府、企业和社会各方的共同努力,在技术、数据、运营等多个层面进行整合,以适应未来低空经济的发展需求。展开更多
基金supported by the National Natural Science Foundation of China 62173337Youth Independent Innovation Foundation of NUDT(ZK-2023-21).
文摘Drones have gradually been employed to search for unknown sources during leakage accidents.However,current studies have mainly focused on the single-source search problem,while in practical situations,the location and quantity of the sources are commonly unknown.Existing multi-source search methods fail to accurately estimate the source term,primarily due to the inefficient utilization of concentration information.This limitation results in sub-optimal drone movement strategies.To address these issues,we propose a Dynamic Likelihood-Weighted Cooperative Infotaxis(DLW-CI)approach.The approach integrates the Infotaxis cognitive search strategy with multi-drone cooperation by optimizing both source term estimation and the cooperative mechanism.Specifically,we devise a novel source term estimation method that leverages multiple parallel particle filters,with each filter estimating the parameters of a potentially unknown source in scenarios.Subsequently,we introduce a cooperative mechanism based on dynamic likelihood weight to prevent multiple drones from concurrently estimating and searching for the same source.The results show that the success rate for the localization of 2-4 diffusion sources reaches 90%,78%,and 42% respectively when employing the DLW-CI approach,achieving a 37%average improvement over baseline methods.Our findings indicate that the proposed DLW-CI approach significantly improves estimation accuracy and search efficiency for multi-drone cooperative multi-source search,making a valuable contribution to environmental safety monitoring applications.
基金supported by Guangdong Basic and Applied Basic Research Foundation(Grant No.2022A1515011313)in part by Guangdong Innovative and Entrepreneurial Research Team Program(Grant No.2019ZT08Z780)in part by Dongguan Introduction Program of Leading Innovative and Entrepreneurial Talents。
文摘During the scenarios of cooperative tasks performed by a single truck and multiple drones,the route plan is prone to failure due to the unpredictable scenario change.In this situation,it is significant to replan the rendezvous route of the truck and drones as soon as possible,to ensure that all drones in flight can return to the truck before running out of energy.This paper addresses the problem of rendezvous route planning of truck and multi-drone.Due to the available time window constraints of drones,which limit not only the rendezvous time of the truck and drones but also the available period of each drone,there are obvious local optimum phenomena in the investigated problem,so it is difficult to find a feasible solution.A two-echelon heuristic algorithm is proposed.In the algorithm,the strategy jumping out of the local optimum and the heuristic generating the initial solution are introduced,to improve the probability and speed of obtaining a feasible solution for the rendezvous route.Simulation results show that the feasible solution of the truck-drones rendezvous route can be obtained with 88%probability in an average of 77 iterations for the scenario involving up to 25 drones.The influence of algorithm options on planning results is also analyzed.
文摘针对低空经济发展涉及的安全管理问题,在总结低空经济相关技术路线原理及落地方案的运行经验,分析低空安防普适性的4个建设方案:雷达与通感一体技术融合方案、广播式自动相关监视技术方案、远程识别技术方案和基于TDOA(time difference of arrival)无线电技术的多源融合方案的基础上,构建无人飞行器探测技术评价指标体系,并建立了一种基于决策试验评估实验室(decision-making trial and evaluation laboratory, DEMATEL)和优劣解距离法(technique for order preference by similarity to an ideal solution, TOPSIS)的多属性评价方法。结果发现,以TDOA为基础的多源融合方案是构建城市低空安防体系的有效路径和普适性方案。研究表明,低空安防体系的建设是一个系统性工程,需要政府、企业和社会各方的共同努力,在技术、数据、运营等多个层面进行整合,以适应未来低空经济的发展需求。
