NDLI: Safe steering of UGVs in polygonal environments

Content Provider	IEEE Xplore Digital Library
Author	Yongsoon Yoon Tokson Choe Yongwoon Park Kim, H.J.
Copyright Year	2007
Description	Author affiliation: Seoul Nat. Univ., Seoul (Yongsoon Yoon)
Abstract	This paper presents an application of a model predictive control for trajectory generation of an unmanned ground vehicle. An optimal tracking problem while avoiding collision with obstacles is formulated in terms of cost minimization under constraints. The cost function includes terms corresponding to the deviation from the desired trajectory, magnitude of the control input, proximity to the obstacles and the final destination point, respectively. Information on obstacles can be incorporated online in the nonlinear model predictive framework and the resulting constrained optimization problem can be solved using nonlinear programming techniques such as augmented Lagrangian. Then kinematic constraints are treated by the Karush-Kuhn-Tucker (KKT) condition. This approach has been applied for generating safe trajectories for the nonlinear dynamics of a vehicle with a nonlinear tire model in a 2D polygonal environment. Simulation results show that the satisfactory performance was achieved in terms of short and safe trajectory satisfying input constraints.
Starting Page	1804
Ending Page	1809
File Size	756840
Page Count	6
File Format	PDF
ISBN	9788995003862
DOI	10.1109/ICCAS.2007.4406638
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-17
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	ICASE
Subject Keyword	Unmanned Ground Vehicle Predictive models Vehicle dynamics Model Predictive Control Lagrangian functions Constraint optimization Vehicle safety Kinematics Cost function Land vehicles Trajectory Obstacle Avoidance Predictive control
Content Type	Text
Resource Type	Article

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