Key points are not available for this paper at this time.
We present a nonlinear model predictive control algorithm for online motion planning and tracking of an omnidirectional autonomous robot. The formalism is based on the minimization of a control Hamiltonian related to the cost function. This minimization is constrained by a nonlinear plant model. The algorithm considers point obstacles and uses a potential field to penalize proximity to those obstacles. A simple and demonstrative example simulation is presented.
Teatro et al. (Wed,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: