Adaptive formation control of autonomous ground vehicles in leader-follower structure

Author(s):  
Gyorgy Max ◽  
Bela Lantos
Robotics ◽  
2018 ◽  
Vol 7 (4) ◽  
pp. 67 ◽  
Author(s):  
Aakash Soni ◽  
Huosheng Hu

Autonomous/unmanned driving is the major state-of-the-art step that has a potential to fundamentally transform the mobility of individuals and goods. At present, most of the developments target standalone autonomous vehicles, which can sense the surroundings and control the vehicle based on this perception, with limited or no driver intervention. This paper focuses on the next step in autonomous vehicle research, which is the collaboration between autonomous vehicles, mainly vehicle formation control or vehicle platooning. To gain a deeper understanding in this area, a large number of the existing published papers have been reviewed systemically. In other words, many distributed and decentralized approaches of vehicle formation control are studied and their implementations are discussed. Finally, both technical and implementation challenges for formation control are summarized.


Author(s):  
Masahiro Ono ◽  
Greg Droge ◽  
Havard Grip ◽  
Olivier Toupet ◽  
Chris Scrapper ◽  
...  

2000 ◽  
Author(s):  
Jeffrey S. Wit ◽  
Carl D. Crane ◽  
Armstrong III ◽  
II David G.

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Hajira Saleem ◽  
Faisal Riaz ◽  
Leonardo Mostarda ◽  
Muaz A. Niazi ◽  
Ammar Rafiq ◽  
...  

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Shuyou Yu ◽  
Matthias Hirche ◽  
Yanjun Huang ◽  
Hong Chen ◽  
Frank Allgöwer

AbstractThis paper reviews model predictive control (MPC) and its wide applications to both single and multiple autonomous ground vehicles (AGVs). On one hand, MPC is a well-established optimal control method, which uses the predicted future information to optimize the control actions while explicitly considering constraints. On the other hand, AGVs are able to make forecasts and adapt their decisions in uncertain environments. Therefore, because of the nature of MPC and the requirements of AGVs, it is intuitive to apply MPC algorithms to AGVs. AGVs are interesting not only for considering them alone, which requires centralized control approaches, but also as groups of AGVs that interact and communicate with each other and have their own controller onboard. This calls for distributed control solutions. First, a short introduction into the basic theoretical background of centralized and distributed MPC is given. Then, it comprehensively reviews MPC applications for both single and multiple AGVs. Finally, the paper highlights existing issues and future research directions, which will promote the development of MPC schemes with high performance in AGVs.


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