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Navigation for precision farming in open fields

We have experience with the ROS navigation stack and with Navigation 2. Together with some developers of robots for agriculture we are looking into the precision navigation in the open fields. Experiments with RTK GPS showed that the precision was not enough. Moreover, the typical 2D lidar based approaches do not work in the fields. Eventually, the robots must be able to navigate over small (visible) tracks in the fields.

The robots we are looking at have 3D camera’s and 2D lidars. I saw the frameworks from automotive sector, such as Autoware and NVIDIA DRIVE, that have nice processing of such data. Therefore, I was wondering if it would be a good idea to integrate functionality from such frameworks for navigation in agriculture.

Do others have experience with precision navigation in open fields and want to share their experiences with us?

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What kind of precision did you get with RTK GPS? Where you far from the base ?

We observed errors up to 20cm. The base was about 20-40 meters away at the side of the field.

Hi there, there are several types of RTK correction … Which one are you using fixed or floating …? The connection is constant …? All of this is very sensitive to the quality of the antennas as well. I use the swiftnav product and it looks very solid. Bye…

If the question is purely about localization the best low cost GPS we have found is the F9P. It is able to hold a position within 2.5cm.

Check out this product from Ardusimple https://www.ardusimple.com/new-product-launch-simplertk2b-v3-zed-f9p-and-zed-f9r/

We have also found that using a survey grade antenna helps with occlusion. https://www.ebay.com/itm/BEITIAN-NEW-3V-18V-CORS-RTK-GNSS-Survey-Antenna-High-precision-gain-ZED-F9P-GPS/223658578365?hash=item34131711bd:g:A7kAAOSwjZFdd2I6

I have had a difficult time using lasers in an open field. There aren’t enough returns to get an accurate position estimate. Also, using an absolute position system like an RTK GPS prevents accumulative position error.

Is your goal to navigate based on these visible tracks and not necessarily base on absolute position?

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You might want to reach out to Univeriste Laval, they do large-scale outdoor mapping: https://norlab.ulaval.ca/publications/penality-icp/ .

Thank you for these pointers.

For the short term, we need to adjust to visible tracks and visible rows of crops. This is because the current rows are not planted automatically and they do not match to the planned absolute positions of the rows according to the map/plan. Eventually, we expect that robots will also saw and plant the crops. In that situation, the absolute position of the rows is known. I assume 2.5 cm would eventually be enough for following the tracks.

Did you think about putting a robotic total station to the field? The robotic ones can track crystals and provide you with milimeter precision. But that, of course, expects direct visibility of the tractors all the time…

But even with some occlusions it could be an interesting problem - whenever there is direct visibility, the total station would tell the robot where it is, and when visual contact is lost, the robot would guide the total station to find it :slight_smile: (providing it its pose estimated from the onboard mapping or row-following algorithm).

We have thought about a total station for experimental settings, e.g. for validating another solution. Is there a total station approach that is aimed at mobile robots? For smaller fields an approach with “normal” high definition cameras might also be a solution. However, ideally we do not use external infrastructure that has to be installed and maintained.