Path Tracking Control for a Wheeled Mobile Robot

2010 ◽  
Vol 29-32 ◽  
pp. 2076-2081 ◽  
Author(s):  
Yuan Liang Zhang

In this paper a model algorithm control (MAC) method is proposed to do the path tracking control of a wheeled mobile robot (WMR). This mobile robot is a three-wheel differentially steered wheeled mobile robot subject to nonholonomic constraints. The kinematic model of this mobile robot is presented and used as the mobile robot model to be controlled. Simulations are conducted to show the performance and feasibility of the proposed control strategy for the path tracking of a wheeled mobile robot.

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 15592-15602
Author(s):  
Xueshan Gao ◽  
Rui Gao ◽  
Peng Liang ◽  
Qingfang Zhang ◽  
Rui Deng ◽  
...  

Author(s):  
J-L Yang ◽  
D-T Su ◽  
Y-S Shiao ◽  
K-Y Chang

This paper presents techniques for building system configuration, control architecture, and implementation of a vision-based wheeled mobile robot (WMR). The completed WMR has been built with the dead-reckoning method so as to determine the vehicle's velocity and posture by the numerical differentiation/integration over short travelling. The developed proportional-integral-derivative (PID) controllers show good transient performances; that is, the velocity of right and left wheels can track the commands quickly and correctly. Moreover, the path-tracking control laws have also been executed within the digital signal processor (DSP)-based controller in the WMR. The image-recognized system can obtain motion information at 15 frames/s by using the hybrid intelligent system (HIS) model, which is one of the well-known colour detection methods. The better performance a vision system has, the more successful the control laws design. The WMR obtains its posture from the dead-reckoning device together with the vision system. These subsystems are integrated, and the operators of the whole system are completed. This WMR system can be thought of as a platform for testing various tracking control laws and a signal-filtering method. To solve the problem of position/orientation tracking control of the WMR, two kinematical optimal non-linear predictive control laws are developed to manipulate the vehicle to follow the desired trajectories asymptotically. A Kalman filter scheme is used to reduce the bad effect of the imagine nose; thereby the accuracy of pose estimation can be improved. The experimental system is composed of a wireless RS232 modem, a DSP-based controller for the WMR, and a vision system with a host computer. A computation-effective and high-performance DSP-based controller is constructed for executing the developed sophisticated path-tracking laws. Finally, the simulation and experimental results show the feasibility and effectiveness of the proposed control laws.


10.5772/6224 ◽  
2008 ◽  
Vol 5 (4) ◽  
pp. 38 ◽  
Author(s):  
Umesh Kumar ◽  
Nagarajan Sukavanam

For a four wheeled mobile robot a trajectory tracking concept is developed based on its kinematics. A trajectory is a time–indexed path in the plane consisting of position and orientation. The mobile robot is modeled as a non holonomic system subject to pure rolling, no slip constraints. To facilitate the controller design the kinematic equation can be converted into chained form using some change of co-ordinates. From the kinematic model of the robot a backstepping based tracking controller is derived. Simulation results demonstrate such trajectory tracking strategy for the kinematics indeed gives rise to an effective methodology to follow the desired trajectory asymptotically.


Author(s):  
Yu Zheng ◽  
Olugbenga Moses Anubi

Abstract Path-tracking control of wheeled mobile robot (WMR) has gained a lot of research attention, primarily because of its wide applicability — for example intelligent wheelchairs, exploration-assistant remote WMR. Recent increase in remote and autonomous operations/requirements for WMR has led to more and more use of IoT devices within the control loop. Consequently, providing interfaces for malicious interactions through false data injection attacks (FDIA). Moreover, optimization-based FDIAs have been shown to cause catastrophic consequences in feedback control systems while by-passing any residual-based monitoring system. Since these attacks target system measurement process, this paper focuses on the problem of improving the resiliency of dynamical observers against FDIA. Specifically, we propose an attack-resilient pruning algorithm which attempts to exclude compromised channels from being processed by the observer. The proposed pruning algorithm improves attack-localization precision to 100% with high probability, which correspondingly improves the resiliency of the underlying UKF to FDIA. The improvements due to the developed resilient pruning-based observer is validated through a numerical simulation of a two-layer path-tracking control platform of differential-driven wheeled mobile robot (DDWMR) under FDIA.


2018 ◽  
Vol 7 (4) ◽  
pp. 2256 ◽  
Author(s):  
Ameer L. Saleh ◽  
Mohammed J. Mohammed ◽  
Ahmed Sabri Kadhim ◽  
Hana’a M. Raadthy ◽  
Hesham J. Mohammed

In this paper, a Fuzzy Neural Petri Net (FNPN) controller has been designed established on Particle Swarm Optimization (PSO) for controlling the path tracking of Wheeled Mobile Robot (WMR). The path planning controller problem has been solved using two FNPN controllers to get the desired velocity and azimuth. The PSO method has used to detection the optimal values parameters of FNPN controllers. The overall models of wheeled mobile robot for path tracking control created on PSO algorithm are implemented in Simulink-Matlab. Simulation outcomes demonstrate the suggested FNPN controllers is more effectiveness and has good dynamic performance than the conventional methods. 


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