Center for Human Modeling and Simulation

Document Type

Conference Paper

Date of this Version

2014

Publication Source

IEEE International Conference on Robotics and Automation (ICRA 2014)

Start Page

1631

Last Page

1638

DOI

10.1109/ICRA.2014.6907070

Comments

ICRA was held May 31-June7, 2014, in Hong Kong.

Abstract

This paper presents a GPU-based wave-front propagation technique for multi-agent path planning in extremely large, complex, dynamic environments. Our work proposes an adaptive subdivision of the environment with efficient indexing, update, and neighbor-finding operations on the GPU to address several known limitations in prior work. In particular, an adaptive environment representation reduces the device memory requirements by an order of magnitude which enables for the first time, GPU-based goal path planning in truly large-scale environments (> 2048 m2 ) for hundreds of agents with different targets. We compare our approach to prior work that uses an uniform grid on several challenging navigation benchmarks and report significant memory savings, and up to a 1000X computational speedup.

Copyright/Permission Statement

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Date Posted: 13 January 2016