Title:
Saliency Detection and Model-based Tracking: a Two Part Vision System for Small Robot Navigation in Forested Environments
Saliency Detection and Model-based Tracking: a Two Part Vision System for Small Robot Navigation in Forested Environments
| dc.contributor.author | Roberts, Richard | |
| dc.contributor.author | Ta, Duy-Nguyen | |
| dc.contributor.author | Straub, Julian | |
| dc.contributor.author | Ok, Kyel | |
| dc.contributor.author | Dellaert, Frank | |
| dc.contributor.corporatename | Georgia Institute of Technology. College of Computing | |
| dc.contributor.corporatename | Georgia Institute of Technology. Center for Robotics and Intelligent Machines | |
| dc.date.accessioned | 2012-09-24T18:55:42Z | |
| dc.date.available | 2012-09-24T18:55:42Z | |
| dc.date.issued | 2012-05-01 | |
| dc.description | ©Copyright 2012 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. http://dx.doi.org/10.1117/12.919598 | en_US |
| dc.description | Presented at Unmanned Systems Technology XIV - SPIE Defense; Security; and Sensing, April 25-27 2012, Baltimore, MD. | |
| dc.description | DOI: 10.1117/12.919598 | |
| dc.description.abstract | Towards the goal of fast, vision-based autonomous flight, localization, and map building to support local planning and control in unstructured outdoor environments, we present a method for incrementally building a map of salient tree trunks while simultaneously estimating the trajectory of a quadrotor flying through a forest. We make significant progress in a class of visual perception methods that produce low-dimensional, geometric information that is ideal for planning and navigation on aerial robots, while directing computational resources using motion saliency, which selects objects that are important to navigation and planning. By low-dimensional geometric information, we mean coarse geometric primitives, which for the purposes of motion planning and navigation are suitable proxies for real-world objects. Additionally, we develop a method for summarizing past image measurements that avoids expensive computations on a history of images while maintaining the key non-linearities that make full map and trajectory smoothing possible. We demonstrate results with data from a small, commercially-available quad-rotor flying in a challenging, forested environment. | en_US |
| dc.identifier.citation | Richard Roberts ; Duy-Nguyen Ta ; Julian Straub ; Kyel Ok and Frank Dellaert, "Saliency detection and model-based tracking: a two part vision system for small robot navigation in forested environment", Proc. SPIE 8387, Unmanned Systems Technology XIV, 83870S (May 1, 2012). | en_US |
| dc.identifier.doi | 10.1117/12.919598 | |
| dc.identifier.uri | http://hdl.handle.net/1853/44943 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.publisher.original | SPIE | |
| dc.subject | Forested environment | en_US |
| dc.subject | Localization map building | en_US |
| dc.subject | Low-dimensional geometric information | en_US |
| dc.subject | Map building | en_US |
| dc.subject | Motion planning | en_US |
| dc.subject | Motion saliency | en_US |
| dc.subject | Navigation | en_US |
| dc.subject | Outdoor environments | en_US |
| dc.subject | Quadrotor | en_US |
| dc.subject | Vision-based autonomous flight | en_US |
| dc.title | Saliency Detection and Model-based Tracking: a Two Part Vision System for Small Robot Navigation in Forested Environments | en_US |
| dc.type | Text | |
| dc.type.genre | Proceedings | |
| dspace.entity.type | Publication | |
| local.contributor.author | Dellaert, Frank | |
| local.contributor.corporatename | Institute for Robotics and Intelligent Machines (IRIM) | |
| local.contributor.corporatename | College of Computing | |
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