Neural Networks Applied to Gait Control of Physically Based Simulated Robots
SBRN '06 Proceedings of the Ninth Brazilian Symposium on Neural Networks
Robust Kalman filter of discrete-time Markovian jump system with parameter and noise uncertainty
SMO'07 Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization
Path following controller for gyroscopically stabilized single-wheeled robot
ACMOS'07 Proceedings of the 9th WSEAS international conference on Automatic control, modelling and simulation
Machine Vision and Applications
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This paper has studied techniques for building system configuration, control architecture and implementation of a vision-based wheeled mobile robot. 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 PID controllers show good transient performances, that is, velocity of right and left wheels can track the commands quickly and correctly. Moreover, the path tracking control laws have been also executed in the DSP-based controller in the WMR. The image-recognized system can obtain motion information 15 [frames/sec] by using HS model, which is one of the well-known color 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. Finally, we integrate these subsystems and complete the operators of the whole system. This complementing wheeled mobile robot system can be thought of as a platform for testing various tracking control laws and signal filtering method. To solve the problem of position/orientation tracking control of the WMR, two kinematical optimal nonlinear predictive control laws are developed to manipulate the vehicle to asymptotically follow the desired trajecto ries. A Kalman filtering scheme is used to reduce the bad effect of the imagine nose, thereby improving the accuracy of pose estimation. The experimental system is composed of a wireless RS232 modem, a DSP -based controller for the wheeled mobile robot 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. Simulation and experimental results are included to illustrate the feasibil ity and effectiveness of the proposed control laws.