Simulating differential games with improved fidelity to better inform cooperative & adversarial two vehicle UAV flight

Anne Redulla, Surya P. N. Singh
{"title":"Simulating differential games with improved fidelity to better inform cooperative & adversarial two vehicle UAV flight","authors":"Anne Redulla, Surya P. N. Singh","doi":"10.1109/SIMPAR.2018.8376282","DOIUrl":null,"url":null,"abstract":"Automatic determination of an areal vehicle's strategy rests on accurate simulation and forecasting to inform control decisions. As system dynamics affect the outcomes, when two or more vehicles interact finding the best strategy to take may be considered a differential game. While traditionally modelled using ideal kinematics, the effect on, and the variation of, the optimal strategy based on simulating realistic dynamics is investigated. A derivation for the optimal strategies of the players in ‘regular’ regions of the state space is completed. Two simulators were developed to compare game terminal results to the theoretical predictions. A MATLAB simulator with ideal player kinematics was the first simulator formed. Then, a high-fidelity simulator, using Microsoft's AirSim project was implemented. This involved configuring AirSim to run using software commands only, and extending the functionality to allow for the simulation of two separately-controlled drones. A trivial differential game with two agile players, termed Pedestrian Tag (PT), was used to identify the accuracy of time-to-capture predictions. The MATLAB simulator was found to match the model prediction, whereas the AirSim simulator required more gameplay time than predicted to achieve capture. For a Homicidal Chauffeur (HC) game, the MATLAB simulator results were consistent with the theoretical predictions. However, multiple outcomes of trials contrasted the predicted terminal results for the high-fidelity simulator. The results indicate that modelling the players to have ideal kinematics does not correctly predict the outcome of a pursuit-evasion game with full/realistic dynamics. Although some deviation from the model assumptions was introduced due to implementation constraints, the primary factor was concluded to be the realistic velocities of the drone agents due to unaccounted dynamics such as inertia and drag. Future research topics prompted by this work include applying the simulation to more differential games, and comparing against player strategies developed from other methods.","PeriodicalId":156498,"journal":{"name":"2018 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIMPAR.2018.8376282","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Automatic determination of an areal vehicle's strategy rests on accurate simulation and forecasting to inform control decisions. As system dynamics affect the outcomes, when two or more vehicles interact finding the best strategy to take may be considered a differential game. While traditionally modelled using ideal kinematics, the effect on, and the variation of, the optimal strategy based on simulating realistic dynamics is investigated. A derivation for the optimal strategies of the players in ‘regular’ regions of the state space is completed. Two simulators were developed to compare game terminal results to the theoretical predictions. A MATLAB simulator with ideal player kinematics was the first simulator formed. Then, a high-fidelity simulator, using Microsoft's AirSim project was implemented. This involved configuring AirSim to run using software commands only, and extending the functionality to allow for the simulation of two separately-controlled drones. A trivial differential game with two agile players, termed Pedestrian Tag (PT), was used to identify the accuracy of time-to-capture predictions. The MATLAB simulator was found to match the model prediction, whereas the AirSim simulator required more gameplay time than predicted to achieve capture. For a Homicidal Chauffeur (HC) game, the MATLAB simulator results were consistent with the theoretical predictions. However, multiple outcomes of trials contrasted the predicted terminal results for the high-fidelity simulator. The results indicate that modelling the players to have ideal kinematics does not correctly predict the outcome of a pursuit-evasion game with full/realistic dynamics. Although some deviation from the model assumptions was introduced due to implementation constraints, the primary factor was concluded to be the realistic velocities of the drone agents due to unaccounted dynamics such as inertia and drag. Future research topics prompted by this work include applying the simulation to more differential games, and comparing against player strategies developed from other methods.
模拟具有改进保真度的差分博弈,以更好地告知合作和对抗两车无人机飞行
车辆策略的自动确定依赖于精确的仿真和预测,从而为控制决策提供信息。由于系统动力学影响结果,当两辆或更多的车辆相互作用时,寻找最佳策略可能被认为是一个微分博弈。在传统的理想运动学建模的基础上,研究了基于仿真现实动力学的最优策略的影响和变化。完成了在状态空间的“规则”区域中参与者的最优策略的推导。开发了两个模拟器,将游戏终端结果与理论预测进行比较。建立了具有理想运动员运动学的MATLAB仿真器。然后,使用微软的AirSim项目实现了一个高保真模拟器。这涉及将AirSim配置为仅使用软件命令运行,并扩展功能以允许模拟两个单独控制的无人机。一个有两个敏捷参与者的微分游戏,称为行人标签(PT),被用来确定捕获时间预测的准确性。发现MATLAB模拟器与模型预测相匹配,而AirSim模拟器需要比预测更多的游戏时间才能实现捕获。对于一个杀人司机(HC)游戏,MATLAB模拟器的结果与理论预测一致。然而,多个试验结果与高保真模拟器的预测最终结果形成对比。结果表明,将玩家建模为具有理想运动学并不能正确预测具有完全/现实动力学的追逐-逃避博弈的结果。尽管由于实施限制,引入了与模型假设的一些偏差,但由于未考虑惯性和阻力等动态因素,得出的主要因素是无人机代理的实际速度。这项工作促使未来的研究主题包括将模拟应用于更多不同的游戏,并与其他方法开发的玩家策略进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信