Randomized model predictive control for robot navigation

— We suggest a new navigation approach to mobile robots, within a nonlinear model predictive control framework where a navigation function is used as a control Lyapunov function. We propose a novel approach to the nonlinear optimization problem, by relaxing it and by using randomized algorithms. The advantage of the proposed combination of navigation functions for robot motion planning with randomized algorithms within an MPC framework, is that the control design offers stability by design, is platform independent, and allows the designer to trade-off performance for (computation) speed, according to the application requirements.

• Type: Conference
• Year: 2009
• Where: ICRA
• Authors: Jorge L. Piovesan, Herbert G. Tanner
• Keywords: Control Lyapunov Function, ICRA 2009, Navigation Functions, Randomized Algorithms, Robotics