Real-time, Distributed, Unmanned Ground Vehicle Dynamics and Mobility Simulation

This paper presents an unmanned ground vehicle for use in outdoor environments. The vehicle features a two-bodied design in which the two bodies can rotate relative to each other about a fixed axis. The vehicle uses tracked locomotion for performance in rugged environments and a linear actuator for control of the bodys’ relative orientation. A spring-damper is used to mitigate vibrations due to surface conditions that would add noise to the sensors. A nonlinear model for the vehicle is introduced, and linearized. Design considerations of the suspension system are discussed, including the reduction of vibrations and the maximization of contact forces. Finally, the vehicle dynamics are simulated for the linear and nonlinear models, and the effectiveness and computation time of the two are compared.

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Real Time Network Implementation for Military Unmanned Ground Vehicle based on Standard Ethernet

The Journal of Korean Institute of Information Technology ◽

10.14801/jkiit.2021.19.10.45 ◽

2021 ◽

Vol 19 (10) ◽

pp. 45-55

Author(s):

Dojong Kim ◽

Namgon Kim ◽

DongWon Yang

Keyword(s):

Real Time ◽

Unmanned Ground Vehicle ◽

Ground Vehicle

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

Volume 3: Multiagent Network Systems; Natural Gas and Heat Exchangers; Path Planning and Motion Control; Powertrain Systems; Rehab Robotics; Robot Manipulators; Rollover Prevention (AVS); Sensors and Actuators; Time Delay Systems; Tracking Control Systems; Uncertain Systems and Robustness; Unmanned, Ground and Surface Robotics; Vehicle Dynamics Control; Vibration and Control of Smart Structures/Mech Systems; Vibration Issues in Mechanical Systems ◽

10.1115/dscc2015-9982 ◽

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.

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