Precision agriculture techniques hold much promise for Idaho specialty crops and will potentially allow growers to maximize yield while controlling crop input costs. While precision agriculture holds great promise, it is challenging to implement in specialty crops because managing specialty crops, such as apples or grapes, typically requires significant manual labor. For example, it is not uncommon for grapes and other fruit to be pruned and/or harvested by hand. Even the seemingly simple task of estimating fruit yield can consume multiple days of a laborer’s time since the fruit on the trees must be manually counted. Therefore, precision agriculture techniques add to an already expensive manual labor burden that specialty crop growers must shoulder. One way that labor costs can be reduced and labor-intensive precision agriculture techniques made feasible is through the use of automation. Robots can cheaply do many manual-labor tasks and significantly enhance the productivity of the specialty crop laborer. While the agriculture industry has seen significant innovation in robotics, many of these robots are intended for standard row-planted crops (e.g., self-driven combines). Therefore, there is a need for robots tailored specifically for the specialty crops grown in Idaho. The purpose of this research project was to design and prototype the IdaBot – a low-cost, autonomous utility robot to assist Idaho specialty-crop growers in the day-to-day maintenance and harvesting of their crops. Although the IdaBot could be used to perform a variety of tasks in both orchards and vineyards, the goal of the first IdaBot prototype is to demonstrate
- autonomous navigation of a vineyard
- precision application of chemicals to grape vines to reduce waste from overspray.
Figure 2: The final IdaBot prototype showing the robotic platform, embedded electronics (microcontrollers and sensors), the RFID reader antennas, and the tank sprayer.
The IdaBot prototype was tested on the NNU campus and at Bitner and Williamson Vineyards prior to its final demonstration for the public at Williamson Vineyard. In the testing and the demonstration, the IdaBot was able to perform the following:
- Read RFID tags attached to the grape trellis and estimate the distance to each tag.
- Sense that it was not centered between the grape trellis rows and make a correction.
- Accurately estimate the distance traveled down the grape trellis row
- Turn on/off the sprayer when passing a certain set of RFID tags
 C. Zhou and J. D. Griffin, "Accurate Phase-Based Ranging Measurements for Backscatter RFID Tags," in IEEE Antennas and Wireless Propagation Letters, vol. 11, pp. 152-155, 2012. Available through IEEEXplore or Disney Research.
These abilities form the core of what must be done for the IdaBot to autonomously navigate a vineyard and apply chemicals. Therefore, we consider the IdaBot prototype a success. Of course, much more work is needed to turn the IdaBot prototype into a commercially viable tool for growers. Improvements that may be pursued in future research or a future commercialization effort include:
- Transferring the RFID navigation technology to a larger robot platform and a larger sprayer. A small tractor would likely be a good choice.
- Optimize the software for speed and robustness.
- Modify the RFID distance estimate algorithm to so that can work while frequency hopping (as required by the FCC for commercial use). Frequency hopping was ignored for the IdaBot prototype to simplify this proof-of-concept project.
Figure 3: One of the RFID tags that was mounted on the grape trellis row to allow the IdaBot to autonomously navigate.
Figure 4: The Idabot navigating a grape trellis row at Williamson Vineyard. The RFID tags are mounted above the grape trellis on white poles. Three pairs of tags can be seen.
Figure 5: An aerial view of the Idabot navigating a grape trellis row at Williamson Vineyard.
Lucas A. Pomeroy - Student
Richard E. Grindstaff III - Student
Cole Logemann - Student
Quentin Fredrick - Student
Dr. Joshua Griffin - PI
Dr. Duke Bulanon - Co-PI