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

共 50 条

[41] Using AADL to model and develop ROS-based robotic application
Bardaro, Gianluca
Matteucci, Matteo
2017 FIRST IEEE INTERNATIONAL CONFERENCE ON ROBOTIC COMPUTING (IRC), 2017, : 204 - 207
[42] Trajectory Tracking for Unmanned Vehicle Based on Model Predictive Control Using Linear Matrix Inequalities
Lei, Zhiling
Tang, Xiaoming
2020 CHINESE AUTOMATION CONGRESS (CAC 2020), 2020, : 698 - 703
[43] Mapping of unknown industrial plant using ROS-based navigation mobile robot
Priyandoko, G.
Ming, T. Y.
Achmad, M. S. H.
4TH INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING RESEARCH (ICMER2017), 2017, 257
[44] LIDAR-based Dynamic Environment Modeling and Tracking Using Particles Based Occupancy Grid
Li, Qiaohui
Dai, Bin
Fu, Hao
2016 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, 2016, : 238 - 243
[45] LiDAR-based simultaneous multi-object tracking and static mapping in nearshore scenario
Yao, Zhiting
Chen, Xiyuan
Xu, Ninghui
Gao, Ning
Ge, Mingming
OCEAN ENGINEERING, 2023, 272
[46] Trajectory Tracking Control for Underactuated Surface Vessels Based on Nonlinear Model Predictive Control
Liu, Chenguang
Zheng, Huarong
Negenborn, Rudy R.
Chu, Xiumin
Wang, Le
COMPUTATIONAL LOGISTICS (ICCL 2015), 2015, 9335 : 166 - 180
[47] Lane Detection and Trajectory Tracking Control of Autonomous Vehicle Based on Model Predictive Control
Hu, Jianjun
Xiong, Songsong
Zha, Junlin
Fu, Chunyun
INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, 2020, 21 (02) : 285 - 295
[48] Quadcopter Trajectory Tracking Control Based on Flatness Model Predictive Control and Neural Network
Li, Yong
Zhu, Qidan
Elahi, Ahsan
ACTUATORS, 2024, 13 (04)
[49] Lane Detection and Trajectory Tracking Control of Autonomous Vehicle Based on Model Predictive Control
Jianjun Hu
Songsong Xiong
Junlin Zha
Chunyun Fu
International Journal of Automotive Technology, 2020, 21 : 285 - 295
[50] Aerosol tracking using lidar-based atmospheric profiling and Bayesian estimation
Elbakary, Mohamed I.
Abdelghaffar, Hossam M.
Afrifa, Kwasi
Rakha, Hesham A.
Cetin, Mecit
Iftekharuddin, Khan M.
OPTICS AND LASER TECHNOLOGY, 2020, 128

← 1 2 3 4 5 →