Global asymptotic stabilization of mobile robot using smooth guidance law

Author(s):  
Ciann-Dong Yang ◽  
Long-Life Shaw ◽  
Jyh-Ching Juang
2016 ◽  
Vol 61 (8) ◽  
pp. 2318-2323 ◽  
Author(s):  
Kenta Hoshino ◽  
Yuki Nishimura ◽  
Yuh Yamashita ◽  
Daisuke Tsubakino

2018 ◽  
Vol 15 (6) ◽  
pp. 172988141881263 ◽  
Author(s):  
Paul Quillen ◽  
Kamesh Subbarao

This article puts forth a framework using model-based techniques for path planning and guidance for an autonomous mobile robot in a constrained environment. The path plan is synthesized using a numerical navigation function algorithm that will form its potential contour levels based on the “minimum control effort.” Then, an improved nonlinear model predictive control approach is employed to generate high-level guidance commands for the mobile robot to track a trajectory fitted along the planned path leading to the goal. A backstepping-like nonlinear guidance law is also implemented for comparison with the NMPC formulation. Finally, the performance of the resulting framework using both nonlinear guidance techniques is verified in simulation where the environment is constrained by the presence of static obstacles.


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