Withdraw
Loading…
The mechanical and algorithmic design of in-field robotic leaf sampling device
Wu, Junzhe
Content Files

Loading…
Download Files
Loading…
Download Counts (All Files)
Loading…
Edit File
Loading…
Permalink
https://hdl.handle.net/2142/110652
Description
- Title
- The mechanical and algorithmic design of in-field robotic leaf sampling device
- Author(s)
- Wu, Junzhe
- Issue Date
- 2021-04-28
- Director of Research (if dissertation) or Advisor (if thesis)
- Chowdhary, Girish
- Committee Member(s)
- Allen, Cody Michael
- Stasiewicz, Matthew Jon
- Department of Study
- Engineering Administration
- Discipline
- Agricultural & Biological Engr
- Degree Granting Institution
- University of Illinois at Urbana-Champaign
- Degree Name
- M.S.
- Degree Level
- Thesis
- Date of Ingest
- 2021-09-17T02:34:23Z
- Keyword(s)
- Leaf sampling
- End effector
- Neural network
- Sensor fusion.
- Abstract
- Leaf samples analysis is a significant tool to acquire the actual nutrition information of crops. After that, farmers can adjust fertilization programs to prevent nutritional problems and improve the yield of crops. The traditional way for leaf sampling is manual, and researchers need to go to the field and use paper hole punchers with a catch-tube to collect leaf samples. The temperature in summer is hot, and some crop like corn is difficult for researchers to walk through, therefore the manual way of leaf sampling is not a good option. In this thesis, an automatic method of leaf sampling is presented to solve the difficulty of leaf sampling. The contributions of this thesis are the following: (1) Build the end effector of leaf sampling device to punch and store leaf samples separately, (2) Train a neural network to detect the leaves with high horizontal level, (3) Combine point cloud data from the depth camera and vison data from the camera via the sensor fusion to get the leaf rolling angle and grasp point. The method in this thesis can produce a consistent leaf rolling angle estimate quantitatively and qualitatively on multiple corn leaves, especially on leaves with multiple different angles.
- Graduation Semester
- 2021-05
- Type of Resource
- Thesis
- Permalink
- http://hdl.handle.net/2142/110652
- Copyright and License Information
- Copyright 2021 Junzhe Wu
Owning Collections
Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at IllinoisManage Files
Loading…
Edit Collection Membership
Loading…
Edit Metadata
Loading…
Edit Properties
Loading…
Embargoes
Loading…