A convergent dynamic window approach to obstacle avoidance

被引：219
作者：
Ögren, P
Leonard, NE
机构：
[1] Swedish Def Res Inst, Dept Autonomous Syst, SE-17290 Stockholm, Sweden
[2] Princeton Univ, Dept Mech & Aerosp Engn, Princeton, NJ 08544 USA
来源：
IEEE TRANSACTIONS ON ROBOTICS | 2005年 / 21卷 / 02期
基金：
美国国家科学基金会;
关键词：
Lyapunov function; mobile robots; model predictive control (MPC); navigation function (NF); obstacle avoidance; receding horizon control (RHC); robot control;
D O I：
10.1109/TRO.2004.838008
中图分类号：
TP24 [机器人技术];
学科分类号：
080202 ; 1405 ;
摘要：
The dynamic window approach (DWA) is a well-known navigation scheme developed by Fox et al. and extended by Brock and Khatib. It is safe by construction, and has been shown to perform very efficiently in experimental setups. However, one can construct examples where the proposed scheme fails to attain the goal configuration. What has been lacking is a theoretical treatment of the algorithm's convergence properties. Here we present such a treatment by merging the ideas of the DWA with the convergent, but less performance-oriented, scheme suggested by Rimon and Koditschek. Viewing the DWA as a model predictive control (MPC) method and using the control Lyapunov function (CLF) framework of Rimon and Koditschek, we draw inspiration from an MPC/CLF framework put forth by Primbs to propose a version of the DWA that is tractable and convergent.
引用
收藏
页码：188 / 195
页数：8
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