Ladybird, intelligent robot for the vegetable industry, Australian Centre for Field Robotics, Sydney, Australia

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Manufacturer - Australian Centre for Field Robotics

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Ladybird: An intelligent robot for the vegetable industry: initial lab trials

Published on May 14, 2014

Meet our newest robot, the Ladybird. We have designed and built this robot as a new research platform to support Australia's vegetable industry. The omnidirectional wheel base allows traversal over most existing farm configurations, treading much more lightly over where existing tractor wheels currently run. In addition to the low weight of the vehicle, the ability to turn each wheel allows precision guidance and manoeuvrability, while minimising damage to the soil. In the undercarriage, the Ladybird carries a variety of optical sensors, including stereo and hyperspectral cameras, and the versatile robot arm enables development in a wide variety of applications, including spraying, weeding, thinning and of course to support harvesting research. We are looking forward to to our first tests on vegetable farm in the coming weeks.

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Ladybird: An intelligent robot for the vegetable industry: motion and autonomy tests

Published on May 28, 2014

Our first full motion test of the ladybird outside. We exercise the whole system for the first time, including translation, rotation and combined manoeuvres, including autonomous row alignment and following.

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Ladybird: part 1 - construction and automation

Published on Jul 8, 2014

We've built the Ladybird: an intelligent robot for the vegetable industry. In part 1, we show the construction and testing of the vehicle on a commercial vegetable near Cowra, New South Wales. The vehicle can drive autonomously up and down rows of a vegetable farm, gathering data that we think will be useful for growers to manage the farm. The Ladybird is a solar electric powered vehicle, and during our three day trip, we didn't need to charge the vehicle once.

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Ladybird: part 2 - data and processing

Published on Jul 8, 2014

In part 1, we show the construction and testing of the Ladybird. In part 2, we show some examples of the types of data we obtain and how it can be processed, to provide useful information to growers.

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Article ""Ladybird" autonomous robot to help out down on the farm"

by Colin Jeffrey
July 2, 2014

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The future of farming - Ladybird robot at work at a field day in Cowra
November 25, 2014

A new robot is set to enhance the productivity of vegetable farms through autonomous crop surveillance.
Developed for the vegetable industry by the Australian Centre for Field Robotics at The University of Sydney, the Ladybird robot supports intelligent software to conduct autonomous farm surveillance, mapping, classification and detection for a variety of different vegetables.

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Concept video: Using robotics to target weeds

Published on Dec 11, 2014

Here’s a demonstration of concept weeding methods using the robotic manipulator on our Ladybird robot. We’ll be doing some field trials early 2015!

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Ladybird: real-time targeted spot spray

Published on Feb 19, 2015

This video shows the Ladybird performing targeted spot spray in real time. In this example, we show real-time results, first in the lab and then on a commercial vegetable orchard in Cowra, NSW, Australia. Ladybird detects the locations of seedlings in 3D using a stereo camera, then fires a small and controllable volume of spray at each target. Coupled with algorithms shown in previous videos for automatic weed detection, this technology can be used to deliver tiny amounts of herbicide exactly where it's needed, anywhere on the farm, allowing a herbicide volume reduction to only 0.01% compared with conventional blanket spraying applications.

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Autonomous in-field plant phenotyping with Ladybird

Published on Jul 3, 2016

This video shows Ladybird robot autonomously scanning a plant phenotype trial. Ladybird trundles up and down every row, gathering data from a suite of on-board sensors including lidar, thermal, hyperspectral, and stereo vision to build a high resolution picture of the crops. This data is then automatically processed to provide plant scientists with statistics about the performance of the crop under different growing conditions.