Center for Human Modeling and Simulation

Document Type

Conference Paper

Date of this Version

11-2013

Publication Source

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Start Page

3332

Last Page

3337

DOI

10.1109/IROS.2013.6696830

Comments

The 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) was held November 3-7, 2013 in Tokyo.

Abstract

Path finding is a fundamental, yet computationally expensive problem in robotics navigation. Often times, it is necessary to sacrifice optimality to find a feasible plan given a time constraint due to the search complexity. Dynamic environments may further invalidate current computed plans, requiring an efficient planning strategy that can repair existing solutions. This paper presents a massively parallelized wavefront-based approach to path planning, running on the GPU, that can efficiently repair plans to accommodate world changes and agent movement, without having to restart the wavefront propagation process. In addition, we introduce a termination condition which ensures the minimum number of GPU iterations while maintaining strict optimality constraints on search graphs with non-uniform costs/

Copyright/Permission Statement

© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Share

COinS
 

Date Posted: 13 January 2016