ROS-based Model Predictive Trajectory Tracking Control Architecture using LiDAR-Based Mapping and Hybrid A* Planning

被引：0

作者：

Guirguis, Silvana ^{[1
]}

Gergis, Mark ^{[2
]}

Elias, Catherine M. ^{[1
]}

Shehata, Omar M. ^{[1
]}

Abdennadher, Slim ^{[2
]}

机构：

[1] German Univ, Multirobot Syst MRS Res Grp, Fac Engn & Mat Sci, Mechatron Dept, Cairo, Egypt

[2] German Univ, Fac Media Engn & Technol, Cairo, Egypt

来源：

2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC) | 2019年

关键词：

Normal Distribution Transform Mapping; A* Path Planning Technique; Model Predictive Control; Autonomous Vehicles; VEHICLE;

D O I：

暂无

中图分类号：

U [交通运输];

学科分类号：

08 ; 0823 ;

摘要：

For the past few decades, autonomous vehicles had been one of the most highlighted fields of attraction to the industrial and research communities. The creation of an autonomous ground vehicle has many challenges. Accordingly, the target of this paper is showing a holistic view over the architecture of an autonomous ground vehicle with the focus on experimental offline mapping and path planning using Normal Distribution Transform (NDT) mapping technique and hybrid A* state lattice technique respectively, in addition to the implementation of Model Predictive Control (MPC) for trajectory tracking control of a golf cart. The proposed techniques were successfully verified for their purposes.

引用

页码：2750 / 2756

页数：7

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