A convergent dynamic window approach to obstacle avoidance

Petter Ögren; Naomi Ehrich Leonard

doi:10.1109/TRO.2004.838008

A convergent dynamic window approach to obstacle avoidance

Petter Ögren, Naomi Ehrich Leonard

Research output: Contribution to journal › Article › peer-review

252 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	188-195
Number of pages	8
Journal	IEEE Transactions on Robotics
Volume	21
Issue number	2
DOIs	https://doi.org/10.1109/TRO.2004.838008
State	Published - Apr 2005
Externally published	Yes

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

Keywords

Lyapunov function
Mobile robots
Model predictive control (MPC)
Navigation function (NF)
Obstacle avoidance
Receding horizon control (RHC)
Robot control

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10.1109/TRO.2004.838008

Cite this

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title = "A convergent dynamic window approach to obstacle avoidance",

abstract = "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.",

keywords = "Lyapunov function, Mobile robots, Model predictive control (MPC), Navigation function (NF), Obstacle avoidance, Receding horizon control (RHC), Robot control",

author = "Petter {\"O}gren and Leonard, {Naomi Ehrich}",

note = "Funding Information: Manuscript received February 19, 2003; revised October 23, 2003. This paper was recommended for publication by Associate Editor Y. Liu and Editor S. Hutchinson upon evaluation of the reviewers{\textquoteright} comments. The work of P. {\"O}gren was supported by the Swedish Foundation for Strategic Research through its Center for Autonomous Systems at the Royal Institute of Technology, Stockholm, Sweden. The work of N. E. Leonard was supported in part by the Office of Naval Research under Grants N00014-98-1-0649 and N00014-01-1-0526, in part by the National Science Foundation under Grant CCR-9980058, and in part by the Air Force Office of Scientific Research under Grant F49620-01-1-0382. This paper was presented in part at the IFAC World Congress, Barcelona, Spain, July 2002, and in part at IEEE IROS, Lausanne, Switzerland, October 2002.",

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doi = "10.1109/TRO.2004.838008",

language = "English (US)",

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N2 - 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.

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A convergent dynamic window approach to obstacle avoidance

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