Case Studies

CNH Industrial

Fully Autonomous Precision Farming

Company Overview

CNH Industrial is a global leader in the capital goods sector with established experience in a wide range of products and a worldwide presence. Each of the individual brands belonging to the company is a major international force in its specific industrial sector: Case IH, New Holland Agriculture, and STEYR for tractors and agricultural machinery; CASE and New Holland Construction for earth moving equipment; IVECO for commercial vehicles; IVECO BUS and Heuliez Bus for buses and coaches; IVECO ASTRA for quarry and construction vehicles; Magirus for firefighting vehicles; Iveco Defense Vehicles for defense and civil protection; and FPT Industrial for engines and powertrain.

CNH Industrial employs some 63,000 people and has 66 manufacturing plants and 53 research and development centers around the world. We have over 6,000 individuals dedicated to innovation, spend some $957 million on R&D annually, and currently hold 9,629 active patents.

Challenges

Today’s companies face complex and interconnected challenges that demand an ever-evolving approach to sustainability, a scenario that CNH Industrial believes is an important driver in creating long-term value for all of its stakeholders.

CNH Industrial operates in a truly inter-connected world, and as a result, pressing global challenges are also at the heart of our business.

  • How are we going to help feed a population of nine billion people by 2050?
  • How are we going to help ensure the required infrastructure in terms of homes, roads, and transport continues to be available?
  • How are we going to help achieve this in a sustainable manner, with an ever-lighter footprint, whilst concurrently delivering productivity and efficiency in every segment and business in which we are present?

Solution

CNH Industrial understands the growing importance of precision farming technologies, and the ever-increasing digitization of the industry is opening up the possibility for significant advances in productivity and efficiency.

Case IH and New Holland, the global agricultural brands of CNH Industrial, were the first to successful demonstrate fully autonomous operation in a row-crop planting application. This solution enables even greater agricultural productivity by ensuring that short operational windows, such as planting periods, are fully leveraged to achieve productivity gains.

One of our key innovation projects is focused on developing enhanced sensing and perception systems to enable vehicles within our agricultural autonomous development program to interpret the agricultural ecosystem in which they are required to operate. CNH Industrial is investigating a range of technology, including Velodyne Lidar sensors.

Within CNH Industrial’s autonomous development program when using the Velodyne sensor, in combination with a range of infrared and visible light spectrum sensors, these concept tractors can scan and monitor their working environments. Based on sensor data, the vehicle informs its supervisor of any unexpected obstacles or problems, which enables work to either continue or for any required corrective action to be carried out.

The information provided by the Velodyne sensor is a key component to facilitating round-the-clock activities, as the sensing and perception system helps avoid and reduce the risks associated with human error in the field. This is a key step in enabling continued industry growth through optimal agricultural production and practices.

Results

By utilizing Velodyne’s lidar technology in our innovation and testing programs, this is helping us, along with other systems, to advance our sensing and perception capabilities. Initially, this was primarily focused on guidance, and now we are developing technologies that also focus on the broader environment in which the machines are operating.

The sensing and perception package is also being integrated into the performance monitoring aspect of our program. Data can be collected around the operating process when conducting operations such as tillage, planting and mowing, and can then be analyzed to both fine tune the equipment to optimize performance. It can also be used to detect eventual operational issues, such as plugging.

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