GPU-Based Dynamic Search on Adaptive Resolution Grids

Loading...
Thumbnail Image
Penn collection
Center for Human Modeling and Simulation
Degree type
Discipline
Subject
Computer Sciences
Engineering
Graphics and Human Computer Interfaces
Funder
Grant number
License
Copyright date
Distributor
Related resources
Author
Garcia, Francisco M.
Kapadia, Mubbasir
Badler, Norman I.
Contributor
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.

Advisor
Date of presentation
2014-01-01
Conference name
Center for Human Modeling and Simulation
Conference dates
2023-05-17T12:40:59.000
Conference location
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Volume number
Issue number
Publisher
Publisher DOI
Journal Issue
Comments
ICRA was held May 31-June7, 2014, in Hong Kong.
Recommended citation
Collection