Obstacle avoidance is achieved by computing disturbance in- variant sets along a nominal trajectory and ensuring these invariant sets do not intersect with ...
A novel technique to compute approximate disturbance invariant sets for general nonlinear systems using a set of finite dimensional optimizations and a ...
This paper describes a tube-based model predictive control (TMPC) approach to robust path tracking and obstacle avoidance for surface vehicles.
Missing: NMPC. | Show results with:NMPC.
A robust nonlinear model predictive controller (RNMPC) is used to help the driver navigating the vehicle in order to avoid obstacles and track the road centre ...
Missing: NMPC. | Show results with:NMPC.
Oct 22, 2024 · This paper proposes a robust control framework for lane-keeping and obstacle avoidance of semiautonomous ground vehicles.
In this paper, we consider the problem of de-centralized control of multi robot systems in the presence of additive bounded uncertainties in the state ...
A robust nonlinear model predictive controller (RNMPC) is used to help the driver navigating the vehicle in order to avoid obstacles and track the road centre ...
The gradientbased MPC methods have been successfully applied to real robotic systems, obtaining smooth collision-free trajectories in the presence of obstacles ...
The main purpose of this paper is to demonstrate that the obstacle avoidance problem in the discrete time setup has considerable structure even when ...
In this paper, we provide a novel robust collision avoidance approach that is based on a general tube-based robust MPC framework. In order to obtain a ...
Missing: NMPC. | Show results with:NMPC.