AI Improving Sensors In The Field
Tim Hammerich
News Reporter
For farmers, dust, branches, and other field obstacles can make it difficult for autonomous equipment to operate effectively. But AI is helping new sensor systems recognize potential roadblocks and respond appropriately, rather than simply bringing a machine to a stop. Bonsai Robotics CEO Tyler Niday explains how that shift makes autonomy more efficient and functional for farmers.
Niday… “ So I think historically, so much of robotics and agriculture have been like a deterministic case where we have a 2D, segmentation map or model, right? Where we detect things in an image like, hey, this is a tree, this is an obstacle, this is a human, and that's all in 2D. And then we have some way to convert it to 3D space to actually navigate—whether it's a LIDAR or stereo vision depth maps. The struggle with those sensors is if there's dust, or if there's debris. We're perceiving in 3D. What we can do now is just start in 3D, right? Like a human doesn't look at an obstacle and be like, ‘Oh, this is a 2D image, and then I need to create the 3D world.’ We have an AI model on our head that says like—has all these associated priors to this model, so we know roughly where it is and what it could be, right? So that's what we're able to do now, and I think that's the big advantage. A lot of ag is all written on historic deterministic stacks that can do one thing, and then you write hundreds of thousands of lines of code to do more. And now we don't have to do it, which is pretty crazy.”
Niday says that this new ability makes the technology better suited for agricultural uses than ever before.
