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In this study, a collision avoidance method with model predictive control is proposed for a nonlinear model of a four-wheeled vehicle. The C/GMRES algorithm is used for solving the nonlinear model predictive control (NMPC) problem within a short sampling period. A nonlinear tire model is employed to represent the realistic behavior of a vehicle. Here, to consider whether it is possible to avoid an...
In this paper a novel method called Sampling-Based Model Predictive Control (SBMPC) is proposed as an efficient MPC algorithm to generate control inputs and system trajectories. The algorithm combines the benefits of sampling-based motion planning with MPC while avoiding some of the major pitfalls facing both traditional sampling-based planning algorithms and traditional MPC. The method is based on...
This paper presents a novel mobile vehicle navigation algorithm based on the stability analysis of the model predictive control approach. The energy-shaping technique is performed with the navigation function to obtain a new virtual vehicle model that generates candidate feasible trajectories for the motion planner. Stability of the nonlinear model predictive control system is obtained by the passivity...
We propose a model predictive control approach to path-following problems of constrained nonlinear systems. We directly consider input and state constraints. Furthermore, we introduce an extended corridor path-following problem, which allows to add spatial degrees of freedom to the path formulation.We give sufficient stability conditions for predictive solutions to 1d and corridor path-following problems...
This paper considers the problem of steering and coordinating a group of omnidirectional mobile robots along given paths. Two subproblems, i.e., a path following subproblem and a motion coordination subproblem are solved by using distributed nonlinear model predictive control (NMPC) whose cost function is coupled with neighbors. The distinct features of NMPC are that constraints can be explicitly...
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