DocumentCode :
2381754
Title :
Randomized model predictive control for robot navigation
Author :
Piovesan, Jorge L. ; Tanner, Herbert G.
Author_Institution :
K&A Wireless LLC, Albuquerque, NM, USA
fYear :
2009
fDate :
12-17 May 2009
Firstpage :
94
Lastpage :
99
Abstract :
The paper suggests a new approach to navigation of mobile robots, based on nonlinear model predictive control and using a navigation function as a control Lyapunov function. In this approach, the nonlinear optimal control problem is treated 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.
Keywords :
Lyapunov methods; control system synthesis; mobile robots; nonlinear control systems; optimal control; path planning; predictive control; random processes; stability; MPC; control Lyapunov function; control design; mobile robot; model predictive control; nonlinear optimal control problem; platform independent; randomized algorithm; robot navigation; stability; trade-off performance; Algorithm design and analysis; Control design; Lyapunov method; Mobile robots; Motion planning; Navigation; Optimal control; Predictive control; Predictive models; Robot motion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2009. ICRA '09. IEEE International Conference on
Conference_Location :
Kobe
ISSN :
1050-4729
Print_ISBN :
978-1-4244-2788-8
Electronic_ISBN :
1050-4729
Type :
conf
DOI :
10.1109/ROBOT.2009.5152468
Filename :
5152468
Link To Document :
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