文章基本信息

标题：Nonlinear Model Predictive Planning and Control for High-Speed Autonomous Vehicles on 3D Terrains
本地全文：下载
作者：Siyuan Yu ; Congkai Shen ; Tulga Ersal 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：20
页码：412-417
DOI：10.1016/j.ifacol.2021.11.208
语种：English
出版社：Elsevier
摘要：AbstractA novel model predictive formulation for autonomous vehicles to plan and execute collision-free and dynamically feasible maneuvers on 3D terrains is introduced. Common approaches for navigating on 3D terrain often rely on graph search techniques or other simplified 2D models to predict the plant behavior. On 3D terrains, it is hard to take vehicle dynamics into account efficiently during planning and control. To address this gap, a vehicle model that considers terrain topology is constructed as the prediction model. A single layer nonlinear model predictive control framework is used to optimize the control inputs of steering rate and longitudinal acceleration based on the newly introduced vehicle model. The new framework is evaluated in simulation on a High Mobility Multipurpose Wheeled Vehicle (HMMWV) climbing on a terrain with varying slopes. Results show that the conventional methods produce failing maneuvers, whereas the new algorithm successfully navigates the vehicle to the target.
关键词：KeywordsAutonomous vehiclesoff-road navigationvehicle dynamicsnonlinear model predictive control