The control of autonomous vehicles is a challenging task that requires advanced control schemes. Nonlinear Model Predictive Control (NMPC) and Moving Horizon Estimation (MHE) are optimization-based control and estimation techniques that are able to deal with highly nonlinear, constrained, unstable and fast dynamic systems. In this chapter, these techniques are detailed, a descriptive nonlinear model is derived and the performance of the proposed control scheme is demonstrated in simulations of an obstacle avoidance scenario on a low-fricion icy road
International audienceIn this paper, a Nonlinear Model Predictive Control (NMPC) has been employed t...
This paper presents a control architecture based on a linear MPC formulation that addresses the lane...
A Model Predictive Control (MPC) approach for controlling active front steering, active braking and ...
In this thesis we consider the problem of designing and implementing Model Predictive Controllers (M...
Abstract—A nonlinear model predictive control algorithm is developed for obstacle avoidance in high-...
The field of autonomous driving vehicles is growing and expanding rapidly. However, the control syst...
Abstract: This paper presents an obstacle avoidance scheme for autonomous vehicles as an active safe...
In this paper we follow the novel approach presented in [1] to autonomous active steering control de...
This paper proposes an algorithm for path-following and collision avoidance of an autonomous vehicle...
The advancement in vision sensors and embedded technology created the opportunity in autonomous vehi...
Full vehicle automation requires complete control over all driving scenarios that can be encountered...
In recent years, research in the field of autonomous driving has been subject to a significant incre...
In this thesis we consider the problem of designing and implementing Model Predictive Controllers (M...
With the advent of faster computer processors and better optimization algorithms, Model Predictive C...
The research field of autonomous vehicle technology has been growing at an accelerated pace. Improve...
International audienceIn this paper, a Nonlinear Model Predictive Control (NMPC) has been employed t...
This paper presents a control architecture based on a linear MPC formulation that addresses the lane...
A Model Predictive Control (MPC) approach for controlling active front steering, active braking and ...
In this thesis we consider the problem of designing and implementing Model Predictive Controllers (M...
Abstract—A nonlinear model predictive control algorithm is developed for obstacle avoidance in high-...
The field of autonomous driving vehicles is growing and expanding rapidly. However, the control syst...
Abstract: This paper presents an obstacle avoidance scheme for autonomous vehicles as an active safe...
In this paper we follow the novel approach presented in [1] to autonomous active steering control de...
This paper proposes an algorithm for path-following and collision avoidance of an autonomous vehicle...
The advancement in vision sensors and embedded technology created the opportunity in autonomous vehi...
Full vehicle automation requires complete control over all driving scenarios that can be encountered...
In recent years, research in the field of autonomous driving has been subject to a significant incre...
In this thesis we consider the problem of designing and implementing Model Predictive Controllers (M...
With the advent of faster computer processors and better optimization algorithms, Model Predictive C...
The research field of autonomous vehicle technology has been growing at an accelerated pace. Improve...
International audienceIn this paper, a Nonlinear Model Predictive Control (NMPC) has been employed t...
This paper presents a control architecture based on a linear MPC formulation that addresses the lane...
A Model Predictive Control (MPC) approach for controlling active front steering, active braking and ...