Software Architecture Proposal for Navigation and Decisions of Autonomous Ground Vehicles in Controlled Environments with Unavoidable Collision Scenarios

2021 ◽  
pp. 270-278
Author(s):  
Mario Alberto Valdes-Saucedo ◽  
Rita Q. Fuentes-Aguilar ◽  
Oscar Carbajal-Espinosa ◽  
Carlos Renato Vazquez
Keyword(s):  
Software Architecture ◽  
Ground Vehicles ◽  
Autonomous Ground Vehicles ◽  
Controlled Environments

Fuzzy Control for Autonomous Ground Vehicles

2000 ◽  
Author(s):  
Jeffrey S. Wit ◽  
Carl D. Crane ◽  
Armstrong III ◽  
II David G.
Keyword(s):  
Fuzzy Control ◽  
Ground Vehicles ◽  
Autonomous Ground Vehicles

scholarly journals Steering Angle Prediction Techniques for Autonomous Ground Vehicles: A Review

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Hajira Saleem ◽  
Faisal Riaz ◽  
Leonardo Mostarda ◽  
Muaz A. Niazi ◽  
Ammar Rafiq ◽  
...  
Keyword(s):  
Ground Vehicles ◽  
Steering Angle ◽  
Autonomous Ground Vehicles ◽  
Prediction Techniques

scholarly journals Model predictive control for autonomous ground vehicles: a review

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Shuyou Yu ◽  
Matthias Hirche ◽  
Yanjun Huang ◽  
Hong Chen ◽  
Frank Allgöwer
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
High Performance ◽  
Control Method ◽  
Theoretical Background ◽  
Future Research ◽  
Centralized Control ◽  
Ground Vehicles ◽  
Uncertain Environments ◽  
Autonomous Ground Vehicles

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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