Novelty-based visual obstacle detection in agriculture
|
Accepted Version
(PDF 950kB)
ICRA_2014_-_Novelty-based_visual_obstacle_detection_in_agriculture.pdf. |
Description
This paper describes a novel obstacle detection system for autonomous robots in agricultural field environments that uses a novelty detector to inform stereo matching. Stereo vision alone erroneously detects obstacles in environments with ambiguous appearance and ground plane such as in broad-acre crop fields with harvested crop residue. The novelty detector estimates the probability density in image descriptor space and incorporates image-space positional understanding to identify potential regions for obstacle detection using dense stereo matching. The results demonstrate that the system is able to detect obstacles typical to a farm at day and night. This system was successfully used as the sole means of obstacle detection for an autonomous robot performing a long term two hour coverage task travelling 8.5 km.
Impact and interest:
Citation counts are sourced monthly from Scopus and Web of Science® citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads:
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
ID Code: | 69391 | ||||
---|---|---|---|---|---|
Item Type: | Chapter in Book, Report or Conference volume (Conference contribution) | ||||
ORCID iD: |
|
||||
Measurements or Duration: | 7 pages | ||||
Keywords: | Computer vision, Field robotics, Obstacle avoidance | ||||
DOI: | 10.1109/ICRA.2014.6907080 | ||||
ISBN: | 978-1-4799-3685-4 | ||||
Pure ID: | 32628189 | ||||
Divisions: | Past > Institutes > Institute for Future Environments Past > QUT Faculties & Divisions > Science & Engineering Faculty Past > Schools > School of Electrical Engineering & Computer Science Current > Research Centres > Centre for Tropical Crops and Biocommodities |
||||
Funding: | |||||
Copyright Owner: | Consult author(s) regarding copyright matters | ||||
Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||||
Deposited On: | 27 Mar 2014 23:43 | ||||
Last Modified: | 02 Mar 2024 17:00 |
Export: EndNote | Dublin Core | BibTeX
Repository Staff Only: item control page