文档名：改进JPS的无人机路径规划研究
摘要：针对传统JPS算法在路径规划时虽然会减少扩展节点的数量,但会使障碍物区域的扩展节点数目增加这一问题,提出了一种改进跳点搜索规则的S-JPS算法.该算法利用基于距离和方向的启发式函数,相比JPS算法可以更准确地描述从当前点到目标点的估计代价,从而减少时间代价、路径代价和拜访节点个数.对于规划出的路径不平滑的问题,提出了基于Bezier曲线和直线混合的轨迹优化方法,将生成的轨迹进行平滑处理,使它的曲率更加连续.仿真实验结果表明,S-JPS算法减少了大量的拜访节点,通过新的跳点规则提高了路径规划的速度.最后,将S-JPS算法应用在自主搭建的无人机上进行实验,在同一规划任务下,S-JPS算法比JPS算法路径规划时间代价减少98.6％,路径代价减少81.1％,拜访节点个数减少99.7％,可以满足无人机在执行飞行任务时对路径规划实时性要求较高的需求.
Abstract：AlthoughthetraditionalJPSalgorithmreducesthenumberofexpansionnodesduringpathplanning,itneedstofindajumppointforeachnodeitgenerates,whichthusincreasesthenumberofexpansionnodesintheobstaclearea,resultinginthetimecostofgeneratingnodesandthepathcost.Andthecostofvisitingnodesishigher.Toaddressthisproblem,thispaperproposesanS-JPSalgorithmthatimprovesthejumpsearchrules.Ontheheuristicfunction:Thisalgorithmintroducesdistanceanddirectioninformation.Thespecificoperationis:Firstmultiplythedistancebetweenthestartingpointandtheendpointbytheweightrepresentingthedistanceinformation,thenmultiplythecosinevalueofthedirectionofthestartingpointandtheendpointbytheweightrepresentingthedirectioninformation,andfinallylinearlycombinetheabovetwosteps.Thecostofgeneratingalargenumberofnodesisreduced.TheJPSalgorithmusesManhattandistanceorEuclideandistancetoestimatethedistancefromthenodetothetargetnodetoevaluatethepriorityofthenodeanddeterminethesearchdirection.Incontrast,theS-JPSalgorithmmoreaccuratelydescribesthedistancefromthecurrentpointtothetarget.Theestimatedcostofthepoint,therebyreducesthetimecost,pathcostandnumberofvisitednodes.Regardingthenodeupdaterules:Inordertoovercomethedifficultyofback-endtrajectoryoptimization,theinflectionpointshavebeentrimmedtofurtherimprovethesmoothnessofthepath.Thespecificoperationsare:Forallextendednodes(a0,a1,···,aN),iftheslopesofthestraightlinesan-1anandanan+1formedbyadjacentnodesaredifferent,connectnodesan-1andan+1.Ifthestraightlinean-1an+1doesnotpassthroughtheobstacle,discardtheoriginalan-1anandanan+1,andretainthelinesegmentan-1an+1.Thenewpathobtainedbyanalogyisthepathobtainedunderthenodeupdaterule.Fortheproblemthatthepathplannedintheback-endtrajectoryoptimizationisnotsmooth,atrajectoryoptimizationmethodbasedonamixtureofBeziercurvesandstraightlinesisproposedtosmooththegeneratedtrajectorytomakeitscurvaturemorecontinuousandthegeneratedtrajectorysmoother.ThisalgorithmrequiresthecurvatureoftheBeziercurvetobecontinuouswiththestraightlinesegment,sothecurvatureattheconnectionbetweentheBeziercurveandthestraightlinesegmentis0.Amongthem,themostimportantpartofusingBeziercurvetoreplacetheoriginalstraightlinesegmentistheselectionofcontrolpoints,andtheselectionmethodofcontrolpointsistheformula(13)inthetext.ThroughsimulationexperimentanalysisandcomparedwiththeJPSalgorithm,ourresultsshowS-JPSalgorithmreducesalargenumberofvisitednodesinthepathplanningunderthesamemap,andimprovesthespeedofpathplanning.Finally,theS-JPSalgorithmisappliedtoandependentlybuiltUAVforexperiments.Underthesameplanningtaskwiththesamestartingpoint,endpointandactualphysicalenvironment,theS-JPSalgorithmreducedsthepathplanningtimeby98.6％comparedtotheJPSalgorithm.Thecostisdownby81.1％andthenumber,ofvisitednodesby99.7％,meetingthehighdemandforreal-timepathplanningofUAVs.
作者：唐嘉宁 闫搏远 陈云浩 颜衡 程俊涛 Author：TANGJianing YANBoyuan CHENYunhao YANHeng CHENGJuntao
作者单位：云南民族大学电气信息工程学院,昆明650000;云南民族大学无人自主系统研究院,昆明650000云南民族大学电气信息工程学院,昆明650000
刊名：重庆理工大学学报
Journal：JournalofChongqingInstituteofTechnology
年，卷(期)：2024, 38(1)
分类号：V249
关键词：跳点搜索算法 Bezier曲线 路径规划 轨迹优化 无人机平台
Keywords：JPSalgorithm Beziercurve pathplanning trajectoryoptimization UAV
机标分类号：
在线出版日期：2024年3月6日
基金项目：国家自然科学基金，国家自然科学基金改进JPS的无人机路径规划研究[
期刊论文] 重庆理工大学学报--2024, 38(1)唐嘉宁 闫搏远 陈云浩 颜衡 程俊涛针对传统JPS算法在路径规划时虽然会减少扩展节点的数量,但会使障碍物区域的扩展节点数目增加这一问题,提出了一种改进跳点搜索规则的S-JPS算法.该算法利用基于距离和方向的启发式函数,相比JPS算法可以更准确地描述从当...参考文献和引证文献
参考文献
引证文献
本文读者也读过
相似文献
相关博文
改进JPS的无人机路径规划研究 Improved UAV path planning study for JPS
改进JPS的无人机路径规划研究.pdf
- 文件大小:
- 6.22 MB
- 下载次数:
- 60
-
高速下载
|
|
