scholarly journals Nonlinear Model Predictive Coordinated Standoff Tracking of a Moving Ground Vehicle

2013 ◽  
Vol 36 (2) ◽  
pp. 557-566 ◽  
Author(s):  
Seungkeun Kim ◽  
Hyondong Oh ◽  
Antonios Tsourdos
Keyword(s):  
Nonlinear Model ◽  
Ground Vehicle ◽  
Standoff Tracking

Nonlinear Model Predictive Controller for an Unmanned Ground Vehicle on Variable Terrain

2015 ◽  
Author(s):  
Andrew Eick ◽  
David Bevly
Keyword(s):  
Real Time ◽  
Nonlinear Model ◽  
Control Algorithm ◽  
Target Location ◽  
Tire Model ◽  
Unmanned Ground Vehicle ◽  
Model Predictive Controller ◽  
Ground Vehicle ◽  
Rollover Risk ◽  
Predictive Controller

Rough, off-road terrain contains multiple hazards for an unmanned ground vehicle (UGV). In this paper, hazards are classified into three groups: obstacles, rough traversable terrain, and rough untraversable terrain. These three types of hazards create a rollover risk for a UGV. A nonlinear model predictive controller (NMPC) that is capable of navigating a UGV through these hazards is presented. The control algorithm features a nonlinear tire model which more accurately captures the dynamics of the UGV when compared to a linearized tire model, and has a fast enough run time for real time implementation. On an actual vehicle, the UGV is assumed to be equipped with a perception based sensor, such as a Light Detection And Ranging (LiDAR) unit, to provide information of the terrain roughness, grade, and elevation. This information is used by the NMPC to safely control the vehicle to a target location. However, for the purposes of this paper, control inputs and terrain are simulated in Car-Sim [1], and the feasibility of real time implementation is investigated.

scholarly journals Fast nonlinear model predictive planner and control for an unmanned ground vehicle in the presence of disturbances and dynamic obstacles

2021 ◽  
Author(s):  
Subhan Khan ◽  
Jose Guivant
Keyword(s):  
Nonlinear Model ◽  
Optimal Path ◽  
Unmanned Ground Vehicle ◽  
Dijkstra Algorithm ◽  
Nonlinear Disturbance Observer ◽  
Ground Vehicle ◽  
Simulation Based ◽  
Processing Resources ◽  
Path Planner ◽  
And Control

Abstract This paper presents a solution for the tracking control problem, for an unmanned ground vehicle (UGV), under the presence of skid-slip and external disturbances in an environment with static and moving obstacles. To achieve the proposed task, we have used a path-planner which is based on fast nonlinear model predictive control (NMPC); the planner generates feasible trajectories for the kinematic and dynamic controllers to drive the vehicle safely to the goal location. Additionally, the NMPC deals with dynamic and static obstacles in the environment. A kinematic controller (KC) is designed using evolutionary programming (EP), which tunes the gains of the KC. The velocity commands, generated by KC, are then fed to a dynamic controller, which jointly operates with a nonlinear disturbance observer (NDO) to prevent the effects of perturbations. Furthermore, pseudo priority queues (PPQ) based Dijkstra algorithm is combined with NMPC to propose optimal path to perform map-based practical simulation. Finally, simulation based experiments are performed to verify the technique. Results suggest that the proposed method can accurately work, in real-time under limited processing resources.

Human Factors Evaluation of 360 Panoramic View Camera System for Ground Vehicle

2007 ◽  
Author(s):  
Cheng Li Wei ◽  
Ang Cher Wee ◽  
Chan Wai Herng ◽  
Ying Meng Fai
Keyword(s):  
Human Factors ◽  
Panoramic View ◽  
Camera System ◽  
Ground Vehicle
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