Randomized Model Predictive Control for Robot Navigation

被引：0

作者：

Piovesan, Jorge L. ^{[1
]}

Tanner, Herbert G. ^{[2
]}

机构：

[1] K&A Wireless LLC, 2617 Juan Tabo NE,Suite A, Albuquerque, NM 87112 USA

[2] Univ Delaware, Dept Mech Engn, Newark, DE 19711 USA

来源：

ICRA: 2009 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-7 | 2009年

关键词：

TRACKING;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：1817 / +

页数：2

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