Trajectory optimization for mobile robots using model predictive control

Robust Trajectory Free Model Predictive Control of Biped Robots with Adaptive Gait Length

This paper employs nonlinear disturbance observer (NDO) for robust trajectory-free Nonlinear Model Predictive Control (NMPC) of biped robots. The NDO is used to reject the additive disturbances caused by parameter uncertainties, unmodeled dynamics, joints friction, and external slow-varying forces acting on the biped robots. In contrary to the slow-varying disturbances, handling sudden pushing ...

Using Model Predictive Control for Local Navigation of Mobile Robots

Model predictive control, MPC, has many interesting features for its application to mobile robot control. It is a more effective advanced control technique, as compared to the standard PID control, and has made a significant impact on industrial process control (Maciejowski, 2002). MPC usually contains the following three ideas: • The model of the process is used to predict the future outputs a...

Trajectory Tracking of Two-Wheeled Mobile Robots, Using LQR Optimal Control Method, Based On Computational Model of KHEPERA IV

This paper presents a model-based control design for trajectory tracking of two-wheeled mobile robots based on Linear Quadratic Regulator (LQR) optimal control. The model proposed in this article has been implemented on a computational model which is obtained from kinematic and dynamic relations of KHEPERA IV. The purpose of control is to track a predefined reference trajectory with the best po...

Model Predictive Control of Nonholonomic Mobile Robots

Model Predictive Control for Mobile Robots with Actively Reconfigurable Chassis

Actively reconfigurable chassis enable planetary mobile robots to access more varieties of terrain. While typical approaches for exploiting such mechanisms reply on feedback control, it is beneficial to consider actively controlled elements at planning time rather than during motion execution. In this paper we present an approach for extending work in model-predictive trajectory generation to a...