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Blog

This video shows the first steps towards an automatic lameness detection system for dairy cows. Four sensors record 3D data as cattle walk past. A Neural Network has been trained with hand-labelled data to detect hooves. These detections are projected to 3D and tracked to provide four hoof trajectories. Limb motion is an important indicator of lameness, and an example of hoof placement is shown for a healthy and severely lame cow.

For more information see our video on youtube or read our paper

 

SwagBot was recently demonstrated at a cattle station near Nevertire, NSW.  SwagBot is a lightweight, electric vehicle designed to collect data on pasture and livestock.  Local farmers were shown how SwagBot can automatically detect and spray weeds in grazing land using various spray attachments.  The team also completed aerial surveying of the property which will be used to develop farm maps and resources for weed mapping.

Thank you to Central West Local Land Services for organising the event.

 

 

The RIPPA team recently completed a successful field trial on a broccoli crop at Fresh Select farms in Werribee, Victoria.  RIPPA's tasks included data collection, foreign object removal, a solar endurance characterization and testing a new deep learning algorithm for weed detection that was used for real time mechanical weeding.

Thanks to the team at Fresh Select for making this possible.

This video shows our latest results in mango fruit detection, localisation and mapping. The multi-sensor robot 'Shrimp' acquires data with a variety of different sensors, including lidar for tree canopy segmentation and colour vision for fruit detection and triangulation. This is arguably the world's most accurate system for mapping individual whole fruit in commercial orchards, while the fruit is still on the tree. Compared to post-harvest yield estimates for individual trees, the system counts accurately (linear fit, near unity slope of 0.96 and r^2 value of 0.89). The system has now been validated on two subsequent seasons, with the third planned later this year (2017). Scanning is performed 2 months before harvest time, meaning there's plenty of opportunity to use it for precision agriculture and on-farm decision making, towards optimised fruit production.

New Ladybird Video

The people from Jungle Creations have taken various footage of our Ladybird robot and made a viral video

https://www.facebook.com/techinsider/videos/837511499780541/

https://www.facebook.com/yooDesignStudio/videos/10154651031221044/

 

Digital Farmhand Video

This video shows footage from a recent demonstration of the Digital Farmhand robot at Richmond, NSW.
Digital Farmhand is a low cost row crop robot aimed towards helping small scale farmers in Australia & overseas to perform crop analytics and automation of simple farming tasks. The design of the platform is based around the use of cheap low cost sensors, computing and manufacturing techniques which will allow the farmer to easily maintain and modify their platform to suit their needs.

The platform comes with an actuated 3 point hitch mechanism which allows various implements to be attached (similar to a tractor). Currently 4 implements have been manufactured for this platform. These include a sprayer, seeder, tine weeder and tow ball hitch.

More details visit http://sydney.edu.au/acfr/agriculture

On the 23rd of June 2017, ACFR was invited to a Local Land Services NSW field day event to present the work they have done over the last six months on a platform called the Digital Farmhand (Previously referred to as Di-Wheel). The event generated a large amount of interest within the local farming community with over 100 registrations for the event. During the event, the team presented:

  • the project overview 
  • the design concept of the Digital Farmhand 
  • plant analytics via low-cost sensors (smartphone camera)
  • the future vision of the project
  • live demonstration of automated row turning via low-cost sensors (smartphone camera)
  • live demonstration of a farming implement (spray boom) mounted on the digital farmhand 

Below are some photos from the event. Link to news article here hawkesbury gazette

Details of the upcoming trial at Richmond of the Digital Farmhand Robot were published in the South West Voice today.

Link to Article

Robotic Arm With Pruner

We had a robotic arm lying around and thought we’d have some fun in the lab with a pneumatic pruner.

Shown here is a UR5 arm configured to navigate to way points on a tree. Once in position, the pruner is activated and a branch is removed.

 

Robotic Arm Picking Apples

We had a robotic arm lying around and thought we’d have some fun in the lab with a new type of gripper.

Shown here is a UR5 arm configured to navigate to way points on a tree. Once in position, the gripper is activated, then the arm twists and pulls the apple from the tree and places the fruit in a tray.

We recently conducted a trial demonstrating the RIPPA robot working on an apple orchard in Three Bridges, Victoria, Australia. RIPPA operated autonomously up and down the apple rows and was able to change rows at the headlands by moving sideways. The trial demonstrated VIIPA autonomously and in real time detecting then targeting apples with variable rates of fluid.

The video below shows some of the experiments conducted on the trial:

Future applications of the technology include pest management, pruning, thinning, and pollinating in tree crop farming. 

In early October, ACFR conducted a series of field trials in Lembang which is located on the outskirts of the city of Bandung Indonesia with the Di-Wheel robot. The objective of the trip was to investigate how robotics can be can be deployed and utilised in a farming context in a developing country. As part of our investigation, a community of local farmers were interviewed to gain a better understanding of their requirements and their situation. We also visited a variety of engineering firms to understand the engineering capabilities within Bandung to support future field trials in that region. 

Below are some videos and photos from the trip.

Tip: Hover cursor over the pictures for the caption

 

mountainous farming area of Bandung Indonesia Chilli crops affected by disease - (Note the yellow leaves)  Di-Wheel with farmers

 

 

 

Interview with the local farmersMost of the farms we visited had very little headland. Every space was utilised to grow crops. We had to assemble our robot on the crop rowDi-Wheel about to start scanning a lettuce row via a smart phone app attached to the robotProfessor Salah Sukkarieh showing the farmers the type of data a robot can collect on their crop rows

Di-Wheel amongst the lettuce Visit to the local dairy farmA type of grass that's fed to the cows

Photo with some of the community membersDi-Wheel - lettuce row scanDi-Wheel with farmersmanual scan over some crops using the AG data logging app for referencing

 

 

 

 

 

 

 

Over the last few months, the RIPPA robot has been working on several commercial vegetable farms around Australia. Various experimental autonomous crop interaction tasks have been demonstrated including:

- autonomous row following and data collection
- autonomous real time mechanical weeding
- autonomous real time variable rate fluid dispensing using VIIPA
- autonomous soil sampling and mapping

Our work was featured in IEEE's Video Friday on November 4, 2016: http://spectrum.ieee.org/automaton/robotics/robotics-hardware/video-friday-rescue-quadruped-gesture-controlled-robot-arm-self-driving-van-1986

View the video below to see RIPPA in action.

The video shows the di-wheel being demonstrated at Cobbity farm (University of Sydney Campus) on a kale crop row.

 

Our initial tests of SwagBot last month have been featured in media outlets around the world.

National articles include: ABC Rural7 NewsTodaySBS and 2Ser

International articles include: New ScientistIEEE SpectrumMashableCNETThe Telegraph UK, Popular Science, Popular MechanicsEngadgetThe EnquirerQuartzGizmodoTech InsiderModern Farmer, New AtlasThe Times of India and Reuters.

Upcoming trials will focus on applying research toward autonomous farm activities including monitoring and interacting with plants and animals.