Team
- Faculty: Manoj Karkee (WSU), Cindy Grimm (OSU), Joe Davidson (OSU), Matthew Whiting (WSU), Stefan Lee (OSU), Sinisa Todorovic (OSU), Heather Knight (OSU)
- Postdoctoral scholar: Salik Khanal (WSU)
- Graduate students: Uddhav Bhattarai (WSU, PhD)
- Undergraduate students: Rachel Stehle (WSU)
Objectives
- Investigate/acquire manual operation and expert knowledge to develop strategies necessary for flower-thinning decision-making.
- Investigate various deep-learning models for detecting and locating flowers and estimating flower cluster orientation and flower density.
- Develop an integrated human-robot collaborative system and evaluate its performance.
Hypotheses
- Human-AI workflows that seek to collaboratively perform thinning tasks can improve productivity and amplify skills in pruning labor.
Approaches
Flower cluster detection and segmentation
Cluster pose (position and orientation) estimation
Flower density estimation, localization, and counting
Early-stage apple flower detection
International Collaboration
AgAID International Collaboration with University of Technology Sidney, Australia
Related Publications
2024
Design, Integration, and Field Evaluation of a Robotic Blossom Thinning System for Tree Fruit Crops Journal Article
In: Field Robotics, 2024, (arXiv:2304.04919 [cs]).
2023
Follow the leader: a path generator and controller for precision tree scanning with a robotic manipulator Proceedings Article
In: Precision agriculture, pp. 167–174, Wageningen Academic Publishers, 2023, ISBN: 978-90-8686-393-8, (Section: 19).
2022
Optical flow-based branch segmentation for complex orchard environments Proceedings Article
In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 9180–9186, arXiv, 2022, (ISSN: 2153-0866).