This paper is concerned with the cooperative target stalking for a multi-unmanned surface vehicle(multi-USV)system.Based on the multi-agent deep deterministic policy gradient(MADDPG)algorithm,a multi-USV target stalki...This paper is concerned with the cooperative target stalking for a multi-unmanned surface vehicle(multi-USV)system.Based on the multi-agent deep deterministic policy gradient(MADDPG)algorithm,a multi-USV target stalking(MUTS)algorithm is proposed.Firstly,a V-type probabilistic data extraction method is proposed for the first time to overcome shortcomings of the MADDPG algorithm.The advantages of the proposed method are twofold:1)it can reduce the amount of data and shorten training time;2)it can filter out more important data in the experience buffer for training.Secondly,in order to avoid the collisions of USVs during the stalking process,an action constraint method called Safe DDPG is introduced.Finally,the MUTS algorithm and some existing algorithms are compared in cooperative target stalking scenarios.In order to demonstrate the effectiveness of the proposed MUTS algorithm in stalking tasks,mission operating scenarios and reward functions are well designed in this paper.The proposed MUTS algorithm can help the multi-USV system avoid internal collisions during the mission execution.Moreover,compared with some existing algorithms,the newly proposed one can provide a higher convergence speed and a narrower convergence domain.展开更多
针对无人水面艇(Unmanned Surface Vessel,USV)航行状态监测及试航性能评估试验中的参数获取问题,设计一套USV航行状态监测系统。以物联网(Internet of Things,IoT)3层架构为基础,设计小尺寸、低功耗的监测方案。以多源传感器和STM32微...针对无人水面艇(Unmanned Surface Vessel,USV)航行状态监测及试航性能评估试验中的参数获取问题,设计一套USV航行状态监测系统。以物联网(Internet of Things,IoT)3层架构为基础,设计小尺寸、低功耗的监测方案。以多源传感器和STM32微控制器作为感知层,以远距离无线电(Long Range Radio,LoRa)网关及LoRa终端作为数据远程传输途径,以传输控制协议(TCP)作为数据远程传输协议,以云平台作为系统应用层,实现数据采集、传输和应用功能。基于监测系统要求,在应用层设置阈值实现航行状态预警功能。对系统功能及性能进行测试,结果表明,系统横、纵摇精度为±0.02°RMS,风速为(0.2±0.03)m/s,风向为±2.5°,所有监测参数技术指标均符合要求,且丢包率在通信距离小于1.4 km时为1.5%,较传统方法降低约22%。该系统可为进一步完善USV航行状态监测提供技术支持。展开更多
基金supported in part by the National Natural Science Foundation of China(61873335,61833011,62173164)the Project of Science and Technology Commission of Shanghai Municipality,China(20ZR1420200,21SQBS01600,22JC1401400,19510750300,21190780300)the Natural Science Foundation of Jiangsu Province of China(BK20201451)。
文摘This paper is concerned with the cooperative target stalking for a multi-unmanned surface vehicle(multi-USV)system.Based on the multi-agent deep deterministic policy gradient(MADDPG)algorithm,a multi-USV target stalking(MUTS)algorithm is proposed.Firstly,a V-type probabilistic data extraction method is proposed for the first time to overcome shortcomings of the MADDPG algorithm.The advantages of the proposed method are twofold:1)it can reduce the amount of data and shorten training time;2)it can filter out more important data in the experience buffer for training.Secondly,in order to avoid the collisions of USVs during the stalking process,an action constraint method called Safe DDPG is introduced.Finally,the MUTS algorithm and some existing algorithms are compared in cooperative target stalking scenarios.In order to demonstrate the effectiveness of the proposed MUTS algorithm in stalking tasks,mission operating scenarios and reward functions are well designed in this paper.The proposed MUTS algorithm can help the multi-USV system avoid internal collisions during the mission execution.Moreover,compared with some existing algorithms,the newly proposed one can provide a higher convergence speed and a narrower convergence domain.
文摘针对无人水面艇(Unmanned Surface Vessel,USV)航行状态监测及试航性能评估试验中的参数获取问题,设计一套USV航行状态监测系统。以物联网(Internet of Things,IoT)3层架构为基础,设计小尺寸、低功耗的监测方案。以多源传感器和STM32微控制器作为感知层,以远距离无线电(Long Range Radio,LoRa)网关及LoRa终端作为数据远程传输途径,以传输控制协议(TCP)作为数据远程传输协议,以云平台作为系统应用层,实现数据采集、传输和应用功能。基于监测系统要求,在应用层设置阈值实现航行状态预警功能。对系统功能及性能进行测试,结果表明,系统横、纵摇精度为±0.02°RMS,风速为(0.2±0.03)m/s,风向为±2.5°,所有监测参数技术指标均符合要求,且丢包率在通信距离小于1.4 km时为1.5%,较传统方法降低约22%。该系统可为进一步完善USV航行状态监测提供技术支持。
