{"title":"Real-time capable path planning for energy management systems in future vehicle architectures","authors":"J. Brembeck, C. Winter","doi":"10.1109/IVS.2014.6856456","DOIUrl":null,"url":null,"abstract":"In this paper an energy optimal path planning and velocity profile generation for our highly maneuverable Robotic Electric Vehicle research platform ROboMObil is presented. The ROMO [1] is a development of the German Aerospace Center's Robotics and Mechatronics Center to cope with several research topics, like energy efficient, autonomous or remote controlled driving for future (electro-) mobility applications. The main task of the proposed algorithms is to calculate an energy optimal trajectory in a real-time capable way. It is designed to incorporate data from actual traffic situations (e.g. oncoming traffic) or changed conditions (e.g. snowy conditions). The resulting trajectory is then fed forward to a lower level time independent path following control [2] that calculates the motion demands for our energy optimal control allocation. This in turn distributes the demand to the actuators of the over-actuated vehicle. We show a numerical reliable way to formulate the energy optimal path planning optimization objective, which is able to provide a consistent replanning feature considering the actual vehicle states. Besides this, different types of optimization methods are evaluated for their real-time capabilities. The velocity profile will be calculated afterwards and the generation of the profile is also enabled to handle dynamic replanning. Finally, we show several experimental results, using a virtual road definition and tests on a commercial real-time platform.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Intelligent Vehicles Symposium Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2014.6856456","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
In this paper an energy optimal path planning and velocity profile generation for our highly maneuverable Robotic Electric Vehicle research platform ROboMObil is presented. The ROMO [1] is a development of the German Aerospace Center's Robotics and Mechatronics Center to cope with several research topics, like energy efficient, autonomous or remote controlled driving for future (electro-) mobility applications. The main task of the proposed algorithms is to calculate an energy optimal trajectory in a real-time capable way. It is designed to incorporate data from actual traffic situations (e.g. oncoming traffic) or changed conditions (e.g. snowy conditions). The resulting trajectory is then fed forward to a lower level time independent path following control [2] that calculates the motion demands for our energy optimal control allocation. This in turn distributes the demand to the actuators of the over-actuated vehicle. We show a numerical reliable way to formulate the energy optimal path planning optimization objective, which is able to provide a consistent replanning feature considering the actual vehicle states. Besides this, different types of optimization methods are evaluated for their real-time capabilities. The velocity profile will be calculated afterwards and the generation of the profile is also enabled to handle dynamic replanning. Finally, we show several experimental results, using a virtual road definition and tests on a commercial real-time platform.