Abstract
In this paper, a two-wheel drive unmanned ground vehicle (UGV) path-following motion control is proposed. The UGV is equipped with encoders to sense angular velocities and a beacon system which provides position and orientation data. Whereas velocities can be sampled at a fast rate, position and orientation can only be sensed at a slower rate. Designing a dynamic controller at this slower rate implies not reaching the desired control requirements, and hence, the UGV is not able to follow the predefined path. The use of dual-rate extended Kalman filtering techniques enables the estimation of the fast-rate non-available position and orientation measurements. As a result, a fast-rate dynamic controller can be designed, which is provided with the fast-rate estimates to generate the control signal. The fast-rate controller is able to achieve a satisfactory path following, outperforming the slow-rate counterpart. Additionally, the dual-rate extended Kalman filter (DREKF) is fit for dealing with non-linear dynamics of the vehicle and possible Gaussian-like modeling and measurement uncertainties. A Simscape Multibody™ (Matlab®/Simulink) model has been developed for a realistic simulation, considering the contact forces between the wheels and the ground, not included in the kinematic and dynamic UGV representation. Non-linear behavior of the motors and limited resolution of the encoders have also been included in the model for a more accurate simulation of the real vehicle. The simulation model has been experimentally validated from the real process. Simulation results reveal the benefits of the control solution.
Highlights
An unmanned ground vehicle (UGV) can be defined as a land-based vehicle that is capable of intelligent motion and action without human input [1]
UGVs can be used in a huge number of applications such as path tracking [2], storage [3], surveillance [4], transportation [5], in unstructured environments [6], and so on
In the path tracking problem, the controller is designed in order to ensure that the UGV is able to follow a predefined sequence of positions and orientations in the plane
Summary
An unmanned ground vehicle (UGV) can be defined as a land-based vehicle that is capable of intelligent motion and action without human input [1]. Rotational velocities are sensed by the encoders at the same rate as the control signal (fast rate), whereas position and orientation are sampled by the beacons at a rate N-times slower than the actuation one (slow rate) This leads to a dual-rate extended Kalman filter (DREKF). The proposed DREKF is featured by: (i) updating the filter gain at every time instant; (ii) resizing the dimension of the gain according to the number of available UGV outputs at every time instant This number will depend on the different sensing rates. Simscape Multibody will be utilized to define some UGV dynamics such as contact forces, non-linear motor behavior, limited encoder resolution, etc, which are difficult to include in the kinematic and dynamic UGV representation In this way, simulation results will accurately reproduce the expectable, real UGV behavior.
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