Motion planning and dynamic control of the Nomad 200 mobile robot in a laboratory environment
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Motion planning and control of a Nomad 200 mobile robot are studied in this thesis. The objective is to develop a motion planning and control algorithm that is able to move the robot from an initial configuration (position and orientation) to a goal configuration in a typical laboratory environment. The robot must be able to avoid unknown static (e.g., walls and tables) and dynamic (e.g., people) obstacles. Dubin's algorithm finds the shortest path connecting two configurations in an obstacle-free environment, but it is not able to avoid obstacles present in the environment. The potential field algorithm is effective in avoiding unknown obstacles, but it has the local minimum problem and does not consider the orientation of a mobile robot. A modified potential field algorithm is first developed. The algorithm overcomes local minima in a typical laboratory environment. The modified potential field algorithm is then combined with Dubin's algorithm to incorporate orientation into motion planning. The combined algorithm is able to avoid static and dynamic obstacles and achieve position and orientation requirements. Simulation and physical experiment results are presented to demonstrate the effectiveness of the algorithm
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