@inproceedings{1e513f0247744b77a8c8f5898feb1a11,
title = "A drift-diffusion model for robotic obstacle avoidance",
abstract = "We develop a stochastic framework for modeling and analysis of robot navigation in the presence of obstacles. We show that, with appropriate assumptions, the probability of a robot avoiding a given obstacle can be reduced to a function of a single dimensionless parameter which captures all relevant quantities of the problem. This parameter is analogous to the P{\'e}clet number considered in the literature on mass transport in advection-diffusion fluid flows. Using the framework we also compute statistics of the time required to escape an obstacle in an informative case. The results of the computation show that adding noise to the navigation strategy can improve performance. Finally, we present experimental results that illustrate these performance improvements on a robotic platform.",
keywords = "Boundary conditions, Collision avoidance, Mathematical model, Navigation, Robot kinematics, Stochastic processes",
author = "Paul Reverdy and Ilhan, {B. Deniz} and Koditschek, {Daniel E.}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015 ; Conference date: 28-09-2015 Through 02-10-2015",
year = "2015",
month = dec,
day = "11",
doi = "10.1109/IROS.2015.7354248",
language = "English (US)",
series = "IEEE International Conference on Intelligent Robots and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "6113--6120",
booktitle = "IROS Hamburg 2015 - Conference Digest",
}