A Convergent Dynamic Window Approach to Obstacle Avoidance
Petter Ogren and Naomi Ehrich Leonard
IEEE Transactions on Robotics and Automation, Volume 21:2, April 2005, 188-195
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 a MPC/CLF framework put forth by Primbs et. al. to propose
a version of the DWA that is tractable and convergent.
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