Bringing Motion Control to the Vineyard: Precision Farming in Action
At Cornell’s Lake Erie Research and Extension Lab, Dr. Terry Bates is transforming grape growing through motion control and robotics. As part of the Efficient Vineyard Project, his team is automating tractors and deploying robotic tool carriers that can navigate vineyard rows, perform targeted tasks, and adjust operations on the fly. By combining environmental sensing with variable-rate technology, these smart machines bring precision, efficiency, and autonomy to viticulture—putting motion control at the heart of modern vineyard management.
“There is a lot of environmental variation on a farm,” said Terry Bates , director of CLEREL. “But it used to be you’d set machines at a particular rate and just go, a ‘one-size-fits-all’ approach. We’ve started to get into precision viticulture, using ag sensors, soil sensors and canopy sensors in order to spatially map the variability in the vineyard.”
Transcript
00:00:04 I'm doctor Terry Bates. I’m a senior research associate in SIPS Horticulture, and I'm the Director of the Cornell Lake Erie Research and Extension Lab located here in Portland, New York. So I've been running a project - I call it a project theme - called the Efficient Vineyard Project, and it's really broken down into measure model and manage. So the first part is to use agricultural sensors to spatially measure the environmental and horticulture variability within a field. We want to know what's going on in that field. Then we layer that spatial data.
00:00:37 So that's the model part is we put that data together. I call viticulture a multi-layer decision making process. So we try to, you know, understand the soil, the canopy, the crop and how that interacts together for better management. And then the manage part is, how to make the machines that we use in the field variable rate so that they respond to the growers decisions which are based on that environmental variation. We just planted a new vineyard and we call it the Tech vineyard. So everything that we can do
00:01:13 in that vineyard with mechanization and robotics, autonomy, sensors, anything that we can put in that vineyard, we will. And we want to evaluate that. This facility, I like to say, is where technology will come to either live or die because we we're putting it into practice and, and some things work, but they're too expensive, so they're not ready for prime time. Other things, are more accessible and they're ready. And they might just need that one little push, for implementation. And that's what we're here for is to help, you know, put that into the hands of the growers so that they can use it.
00:11:11 what? Yeah. So each one of those areas have now brought in collaborators in different areas. So from like the measure standpoint, we work with Katy Gold and Yuja Wang. And Lin says no Ski and Cornell Agritech to measure different things. So stuff like nutrient deficiencies or early disease detection are all different sensors that are being developed, in Geneva that we will apply to our overall program here. And then from the automation standpoint.
00:11:45 So we use a lot of work in vineyard mechanization. So big tractors and heavy equipment. And we want to automate that. We want to take the human out of it and start using robots. So our collaborator Yu Zhang at Cornell Agritech has been using what I call robotic tool carriers. So a robot that you can program to drive up and down the vineyard rows. And what we want to do is start putting equipment on that robot to do small tasks in the vineyard to get, you know, into that area of research and then start upscaling it to more complicated things.
00:12:36 today? Yeah. So mainly we support the juice grape industry and wine grape industry in western New York with all sorts of work in viticulture, just production management, specifically, my program focuses in on what we call the Efficient Vineyard project, or now the efficient vineyard theme that's been going on, since 2015. And that project really focuses in on precision viticulture, and we break it down into measure, model and manage. So we use agricultural sensors to measure what the environmental
00:13:09 and horticulture variability is within the field. And then we process that spatial data. So we model the data. We validate it with in-field measurements to actually turn it into information. We can use. And then the third part, the managed part is to take the agricultural equipment that we use every day and make it variable rate, so that now I can apply the best management, but I can do it variable rate throughout the vineyard depending on what the vineyard needs.