Path-tracking controller design and implementation of a vision-based wheeled mobile robot

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.

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. 


Author(s):  
Sun Qinpeng ◽  
Wang Zhonghua ◽  
Li Meng ◽  
Liu Bin ◽  
Cheng Jin ◽  
...  

2015 ◽  
Vol 13 (4) ◽  
pp. 897-905 ◽  
Author(s):  
Spandan Roy ◽  
Sambhunath Nandy ◽  
Ranjit Ray ◽  
Sankar Nath Shome

1996 ◽  
Vol 8 (1) ◽  
pp. 93-103
Author(s):  
Masafumi Hashimoto ◽  
◽  
Fuminori Oba ◽  
Yasushi Fujikawa ◽  
Kazutoshi Imamaki ◽  
...  

This paper describes a position estimation method for a wheeled mobile robot by integrating information in an odometric dead reckoning and a laser navigation system. Dead reckoning regularly gives the robot positions by the rotational counts of the two side wheels. The laser navigation system successively observes the bearing angles relative to the corner cube reflectors fixed in the robot environment. The chi-squared hypothesis testing is applied to reliably identify the corner cubes. The identified angle measurements modify the robot positions calculated by the dead reckoning based on the Extended Kalman filtering. A plant model is introduced from the kinematic equation concerning the dead reckoning, which-regards both the robot position and the wheel’s radius as state variables and the encoder measurement as an input variable. A measurement model is built concerning the bearing to a corner cube reflector in the environment observed by the scanned laser. The proposed method enables the robot to accurately estimate its position even under uncertainty of the wheel’s radius and the robot motion with slippage in a cluttered environment. The simulation and experimental results justify the proposed method.


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