Departmental Papers (ESE)


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We construct a sensor-based feedback law that provably solves the real-time collision-free robot navigation problem in a compact convex Euclidean subset cluttered with unknown but sufficiently separated and strongly convex obstacles. Our algorithm introduces a novel use of separating hyperplanes for identifying the robot’s local obstacle-free convex neighborhood, affording a reactive (online-computed) piecewise smooth and continuous closed-loop vector field whose smooth flow brings almost all configurations in the robot’s free space to a designated goal location, with the guarantee of no collisions along the way. We further extend these provable properties to practically motivated limited range sensing models.

Sponsor Acknowledgements

This work was supported in part by AFOSR under the CHASE MURI FA9550-10-1-0567.

Document Type

Conference Paper

Subject Area

GRASP, Kodlab

Date of this Version



Note: This paper was nominated for the Best Paper Award at the 12th International Workshop on the Algorithmic Foundations of Robotics in 2016.

Bib Tex

author = {Omur Arslan and Daniel E. Koditschek},
title = {Sensor-Based Reactive Navigation in Unknown Convex Sphere Worlds},
booktitle = {The 12th International Workshop on the Algorithmic Foundations of Robotics},
year = {2016},
month = {December}



Date Posted: 09 November 2018