Robots are beginning to be a part of our daily lives. Although, this has been the case for industrial production for many years, the use of mobile robots has been restricted to very few, specific applications. Research and development of mobile robots has led to improvements in many areas including controls. In order to design a controller for a mobile robot to achieve autonomy, an accurate model must be developed. Similar to any dynamic system, a big trade-off that needs to be made while modeling a robot is between model fidelity and its computational complexity. Kinematic robot models are most commonly-used tools for the analysis and control design. These models, however, might not be able to fully capture the robot behavior. Dynamic models, on the other hand, can be more accurate in capturing the dynamics of robot motion and all the external forces acting on it. These models are typically in the form of nonlinear equations and can impose high computational burden on the system. In this thesis, kinematic and dynamic models for a differential-drive mobile robot are developed, validated, and compared. Despite higher fidelity of dynamic models, it is seen that for common mobile robot tasks, kinematic models might be sufficient, especially considering their control-oriented nature. Based on this observation, a kinematic model is developed for a more advanced omnidirectional mobile robot. This model is then used to implement go-to-goal controllers based on traditional PID and model predictive control design. The controllers' implementation is validated in Matlab/Simulink. This work provides a foundation for future research on modeling and control design for mobile robots.
|Commitee:||Gu, Kequin, Zhang, Mingshao|
|School:||Southern Illinois University at Edwardsville|
|School Location:||United States -- Illinois|
|Source:||MAI 58/04M(E), Masters Abstracts International|
|Subjects:||Mechanical engineering, Robotics|
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