Implementation of nonlinear model predictive control on all terrain mobile robot

Farooqi, Zohaib H. (2017) Implementation of nonlinear model predictive control on all terrain mobile robot. Masters thesis, Memorial University of Newfoundland.

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Abstract

The objective of this thesis is to control a mobile robot with nonholonomic constraints to achieve two control objectives: point stabilization and trajectory tracking. This research adopts Nonlinear Model Predictive Control (NMPC) to achieve these control objectives. The mobile robot platform used in the research is Seekur Jr., which is a skid-steering all terrain mobile robot with nonholonomic constraints. In this study NMPC is developed and tested for both indoor and outdoor navigation. To address the indoor localization issues, two methods have been adopted. In the former approach for indoor localization, a map of the environment is generated using a laser range finder. This map, along with laser range finder, is used to determine the pose (position and orientation) of the mobile robot in the environment. In the second approach, OptiTrack motion capture system has been used, which gives the position data of the mobile robot in the environment and orientation is evaluated through this. For outdoor navigation, Global Positioning System (GPS) is used to obtain the localization. The implementation of NMPC involves solving a dynamic optimization control problem, which makes the evaluation of control command time consuming. Therefore, it is difficult to implement NMPC for mobile robots in real-time applications. To address this issue, an open source toolkit solving Optimal Control Problem (OCP) has been used to implement fast NMPC routine, which provides real-time applicability of the control strategy. Obstacle avoidance feature is also added to the controller to avoid static obstacles in the trajectory of the mobile robot. The proposed control strategy is evaluated on a number of simulations and experimental studies. The results validate the real-time applicability of the proposed approach in indoor and outdoor navigation.

Item Type: Thesis (Masters)
URI: http://research.library.mun.ca/id/eprint/12686
Item ID: 12686
Additional Information: Include bibliographical references (pages xiv-xx).
Department(s): Engineering and Applied Science, Faculty of
Date: May 2017
Date Type: Submission

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