Archives August 2017

Fully driverless combine harvester by 2024

Fully driverless combine harvester by 2024

Published on AGRILAND.IE
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An off-the-shelf combine harvester has been converted to automatically steer itself by a Russian technology company, at a “fraction of the normal cost of such technology”.

This, says the company, is a precursor to fully autonomous (driverless) operation in the near future.

The company is called Cognitive Technologies; it develops robotic systems and software.

What are the advantages of such developments? The company claims that the use of such technology can increase output and reduce losses. It allows the combine harvester operator to “focus on machine settings, rather than steering and driving”.

Working in “low-growth” barley (standing just 30cm tall), the challenge was to come up with a practical system using only one video camera, instead of a plethora of cameras and sensors. In effect, the company says that its system employs only one camera and a “neural network”, unlike “much more expensive” systems from mainstream machinery manufacturers.

According to the company, the system works to a high level of accuracy – targeting a sub-5cm tolerance. The current system automatically stops the combine harvester upon completing each task – awaiting intervention by the driver. A task could encompass multiple rounds of a field.

Olga Uskova, President of Cognitive Technologies, explained: “We’ve spent five years developing this technology thus far. We expect to create a fully autonomous grain harvester by 2023-2024.

“We have already created a highly-developed computer vision system that allows just one camera to achieve similar results as leading international manufacturers get with three to four sensors. As a result, the cost of the equipment is three to four times lower. And this gives us a significant competitive advantage,” she added.

The company field-tested its equipment during recent weeks; the system was fitted to a Russian-built Rostselmash RSM 181 Torum harvester. The tests were carried out in the Rostov region of southern Russia.

Over the course of one and a half days, the system was “re-trained” from wheat to barley. At present, it recognises the edge of the crop, thus determining where the machine should steer itself. According to the company, it can do this “better than a human driver”.

The camera and associated software can identify all manner of obstacles including: uncut versus cut areas; swaths or layers of straw; trees; roadways; people; etc.

Russians test driverless harvester

Russians test driverless harvester

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Russia has stepped into the era of automated machinery with a Russian company field testing an autonomous grain harvester.

Cognitive Technologies, which develops robotic systems and software for machine vision, has field tested a Rostselmash RSM 181 Torum harvester in the Rostov region of Southern Russia.

Company president, Olga Uskova, said the company had spent more than five years developing the system and expected to have a fully autonomous grain harvester available for commercial release by 2023-2024.

She said the system was low-cost because it used a single video camera as a sensor, unlike other systems that used laser scanners, stereo cameras, lidars (light detection and ranging), etc.

“The automated complex of our smart harvester includes a video camera and artificial intelligence system,” she said.

“The neural network of the system is now able to allocate five main classes of the field scene:

1) Unmowed part of the field

2) Mowed part of the field

3) Roll in the hay

4) Everything that falls in the view of the camera from the header of the harvester

5) All other objects – obstacles, other machinery, forests, trees, roads, weeds, people etc.

“The additional competitive advantage of our Ai system is that it sees various types of field boundaries (edges, rolls).”

Mrs Uskova said in the field tests, instead of the planned field of wheat that would have been more than 80 centimetres high, farmers provided fields of barley that were about 30 cm high.

“This was a great, almost impossible challenge. For 1.5 days we retrained the neural network based on the datasets of other agro cultures. As a result, the neural network was able to determine the stacked roll and the field scene better than the person. The result surpassed all expectations. This is a breakthrough,” she said.

VisionHack – First international hackathon on computer vision for unmanned vehicles

VisionHack – First international hackathon on computer vision for unmanned vehicles

Published on SOCIABLE.CO
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Recently, the words “Russia” and “Hack” have been paired together in the news with some pretty negative stigma, however VisionHack presents a different narrative regarding hacking in the Russian capital.

VisionHack will be the first university hackathon focusing on artificial intelligence and computer vision with prizes of more than $30,000.

The Moscow based competition will take place from September 11th-13th and will attract talent from around the world such as teams from MIT (USA), the University of Cambridge (UK), the University of Science and Technology Beijing (P.R. China), UPC (Spain) along with a number of university teams from Russia.

The competition will be jointly organized by NUST MISIS, one of Russia’s leading technology universities, and Cognitive Technologies, a company which develops AI systems for unmanned vehicles.

According to Alevtina Chernikova, Rector of NUST MISIS: “It is not a coincidence that Russia and NUST MISIS have become a venue for holding such high-level events-Russia has one of the world`s best schools for the development of artificial intelligence. Today, our domestic developments in the field of computer vision are highly rated by leading international experts, and the NUST MISIS team for several years in a row has reached the final of the ACM/ICPC international programming championship”.

The participants’ task will be to create their own intellectual subsystem for driver assistance and ADAS (advanced driver assistance system) capable of automatically detecting various events of the road such as: a car stopped in the middle of the street with its hazard lights on; or a dog or small child about to cross the street, essentially anything that might pose as a conventional danger within a street setting.

“Participants will have to solve real and significant practical issues of computer vision for unmanned vehicles”, said Olga Uskova, president of the Cognitive Technologies group.

The team which presents the most accurate and comprehensive solution to the set of proposed road situations will be crowned the winner and secondary prizes will be awarded for qualitative decisions on specific developments.

This is the first hackathon in the world dedicated to computer vision technologies and unmanned vehicles. Within recent years, the focus on technology related to unmanned vehicles has been a point of interest for tech giants and governments everywhere such as Lyft and Uber, who have announced ambitions to advance their own self-driving technology. Moreover, experts expect self-driving technology to be one of the biggest technological advances by 2021, making the need for this competition all the more relevant.