Abstract
The paper describes trajectory generation and tracking control algorithms, respectively based on nonlinear filtering and dynamic feedback linearization, for mobile robots. A main feature of proposed algorithms is that they are suitable for the implementation on embedded systems with limited computational resources. The trajectory generator is based on nonlinear filters and logic-based management of reference inputs and dynamic constraints, allowing online smoothing of straight-line reference paths. Sparse via-points along a path can be assigned by a global planner based on obstacle avoidance algorithms and can be changed at any time during motion. Moreover, the trajectory generated by the nonlinear filter can be fed into a control loop based on the dynamic model of the robot, so that accurate tracking can be achieved. The paper includes practical remarks for efficient fixed-point implementation of the proposed trajectory generator.
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