In Search of Farm Robots: Ch 1

A version of this article previously appeared in The Grower

Dan Bloomer has been travelling in Australia and Europe asking, “How ready are robots for farmers and how ready are farmers for robots?”

Notable areas of active research and development globally are scouting, weeding and fruit picking.  Success requires machines that can determine and follow a route traversing whatever terrain it must, capture information, identify and selectively remove weeds, and identify, pick and transport fruit.  They have to sense, analyse, plan and act.

Robotics is widespread in industries such as car manufacturing that have the exactly the same task being repeated over and over again. With possible exception of robotic milking, farm operations are not like that. Virtually every single case is unique with unique responses needed.

Many groups around the world are looking at robotic weeding . There are many items needing attention. How do we tell weeds from crop plants? Can we do that fast enough and reliably enough to make a robot commercially viable on-farm? Once identified, how do we optimise robotic arm movement to best attack a patch of weeds?

The Australian Centre for Field Robotics (ACFR) at the University of Sydney is well known for its field robots such as the solar powered Ladybird. The new generation Ladybird is known as Rippa, and is currently undergoing endurance testing. Look on YouTube for ACFR videos and you’ll even see SwagBot moving around rolling hill country.

A key theme for Rob Fitch and colleagues is Active Perception: perception being what we can detect with what accuracy and confidence; active meaning in real time and including planning actions. They invest heavily in developing mathematics to get fast results. And they are succeeding.

Using Intel’s RealSense structured light camera it takes them less than half a second to identify and precisely locate groups of apples on a trellis. Within that time they also calculate exactly where to place the camera to get a second confirming view.

Smart maths allow ACFR scientists to capture 3D images and identify and locate apples in less than half a second
Smart maths allow ACFR scientists to capture 3D images and identify and locate apples in less than half a second

Cheryl McCarthy and colleagues at the National Centre for Engineering in Agriculture (NCEA) are conducting a range of research projects that integrate autonomous sensing and control with on-farm operations to robotically manage inputs within a crop. Major projects include automation for weed spot spraying, adaptive control for irrigation optimisation, and remote crop surveillance using cameras and remotely piloted aircraft.

At LandWISE 2015, Cheryl reported on their machine vision and sensing system for weed detection systems that uses depth and colour segmentation and a new processing technique to operate at commercial ground speeds of 10-15 km/h.

Now Cheryl is using UAVs to capture photos of crops, stitching the pictures to get a whole paddock image, then splitting it up again to efficiently identify and locate individual plants and weeds. This is enabling her to create accurate maps some other weed destroying robot can use.

cherylmccarthy
Research at the University of Southern Queensland investigates UAVs to scout paddocks combined with image stitching and analysis for interpretation to create maps of weeds for later treatment

SwarmFarm founders, Andrew and Jocie Bate grow cereals and pulses near Emerald. Spray-fallow is used to conserve water in this dryland environment and WeedSeeker® and Weedit® technologies reduce chemical use to a very small percentage of traditional broadcast application.

4WD SwarmFarm robots carrying WeedSeeker technology cover the paddock spraying only living weeds
4WD SwarmFarm robots carrying WeedSeeker technology cover the paddock spraying only living weeds

With large areas, most growers move to bigger machinery to maximise labour efficiency. This has a number of adverse effects including significant soil damage and inability to work small areas or work efficiently around obstacles such as trees.

SwarmFarm chose robots as practical light weight equipment. They reason that several small machines working together reduce soil impact and have the same work rate as one big machine. Andrew estimates that adoption of 8 m booms versus 34 m booms could increase the effective croppable area in Queensland by 2%.

Are these robots ready for farmers? Are farmers ready for these robots?

Only SwarmFarm has multiple machines currently working on farm in Australia. They are finalising a user interface that will allow non-graduate engineers (smart farmers) to manage the machines.

The question that remains is, “Why would I buy a specialised machine when I can put a driver on a cheaper conventional tractor or higher work rate sprayer and achieve the same?”

Is it the same?

Travel to Australia was supported by a Trimble Foundation Study Grant