• norsk
    • English
  • English 
    • norsk
    • English
  • Login
View Item 
  •   Home
  • Fakultet for informasjonsteknologi og elektroteknikk (IE)
  • Institutt for teknisk kybernetikk
  • View Item
  •   Home
  • Fakultet for informasjonsteknologi og elektroteknikk (IE)
  • Institutt for teknisk kybernetikk
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Perception for obstacle-aided locomotion of snake robots

Lerø, Fredrik Leine
Master thesis
Thumbnail
View/Open
16540_FULLTEXT.pdf (18.33Mb)
16540_ATTACHMENT.zip (181.2Mb)
16540_COVER.pdf (1.556Mb)
URI
http://hdl.handle.net/11250/2458491
Date
2017
Metadata
Show full item record
Collections
  • Institutt for teknisk kybernetikk [4086]
Abstract
The goal of this project was to provide an obstacle-aided snake robot with improved perceptual capability. This implies ensuring that objects located in the snakes' close proximity get a high resolution digital representation. Kintinuous, an algorithm used for mapping an unknown environment while at the same time keeping track of an agents location within it, is the perceptual system of the snake robot. The algorithm maps the environment by getting RGB-images and depth data from a depth sensor called Kinect. The Kinect has a limited range for where it can obtain depth data. Objects located outside this limited range will get a low resolution digital representation, or no representation at all. To compensate for this limited range, Kintinuous was altered by adding a new system component responsible for

computing depth maps with high resolution at lower ranges. The depth maps were computed by using stereo vision principles. The Kinect has a single RGB-camera that is used to capture two different views of the scene, at different times. The new system component then proceeds to compute the matrix relating the two different views in pixel coordinates, by exploiting the Kintinuous tracking information. The images are then rectified to make them row aligned, a dense disparity map computed by matching corresponding pixels, and a depth map acquired.

The results of each part of the system showed the rectification to be inaccurate, resulting bad performance of the matching algorithm. This lead to depth maps being very noisy or completely useless. The depth map fusing was with Kintinuous was though never achieved.

Further work is necessary to make this work as intended, and this thesis is believed to form a good basis for the development of a capable algorithm.
Publisher
NTNU

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit
 

 

Browse

ArchiveCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsDocument TypesJournalsThis CollectionBy Issue DateAuthorsTitlesSubjectsDocument TypesJournals

My Account

Login

Statistics

View Usage Statistics

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit