{"title":"Short-term Path Planning with Multiple Moving Obstacle Avoidance based on Adaptive MPC","authors":"Alberto Franco, Vítor M. F. Santos","doi":"10.1109/ICARSC.2019.8733653","DOIUrl":null,"url":null,"abstract":"This paper presents a different strategy for a self-driving car short-term path planning among multiple moving obstacles. The main task is to study and implement a motion planning and execution framework in order to make ATLASCAR2 coexist with other moving obstacle vehicles by avoiding collision and overtake them when necessary and possible. The proposed technique, based on the Model Predictive Control paradigm, solves an optimization problem formulated in terms of cost minimization under constraints. Simulation results demonstrate and verify the feasibility and the usefulness of the method considering different scenarios, opening space for real scenario implementation.","PeriodicalId":198320,"journal":{"name":"2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)","volume":"28 23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARSC.2019.8733653","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
This paper presents a different strategy for a self-driving car short-term path planning among multiple moving obstacles. The main task is to study and implement a motion planning and execution framework in order to make ATLASCAR2 coexist with other moving obstacle vehicles by avoiding collision and overtake them when necessary and possible. The proposed technique, based on the Model Predictive Control paradigm, solves an optimization problem formulated in terms of cost minimization under constraints. Simulation results demonstrate and verify the feasibility and the usefulness of the method considering different scenarios, opening space for real scenario implementation.