From what we know AJX looks out front in autonomous driving“While many agricultural machinery manufacturers are still in the project or pilot phase, particularly due to the lack of legal certainty surrounding autonomous driving in the public realm, autonomous driving is already part of daily life in open-cast mining. In the massive raw material mines operated by Australian mining company Rio Tinto in Australia, for example, autonomous Komatsu dumper trucks fitted with the Autonomous Haulage System (AHS) transport iron ore without a driver at the wheel. They find their way with the aid of high-precision GPS, while radar and laser sensors enable them to detect obstacles.”
https://www.agritechnica.com/en/news/networking-and-automation On the road to market-ready solutions However, these high-performance assistance systems not only ensure increased safety and better efficiency on fields or construction sites: they are also aimed at paving the way to autonomy.
When this objective is transferred to the system architecture of tractors, harvesting machines or excavators, it means that an increasing volume of data originating from a growing number of sensors is being processed. Ultimately, this information has to be presented intuitively to the operator on the display in the cockpit. SYSTEMS & COMPONENTS will be providing a look ahead to what can be anticipated in this regard over the next few years in the off-highway sector – because the next generation of self-propelled vehicles will be able to move and operate autonomously.
Increased freedom and comfort in steering Discussion surrounding, and interest in, digital steering, driving and brake systems is likely to pick up pace significantly at the trade fair grounds in Hanover, because the suppliers of these technologies have their sights set firmly on series production maturity for the off-highway markets.
Unlike in the automotive sector, retrofit solutions are often in demand here, because operators are not interested in replacing their entire vehicle fleet simply for the sake of autonomous driving. The systems on show will encompass the entire process from the steering wheel and the brake pedal to the axle, and enable immediate tactile feedback of the forces directly to the vehicle operator. Implementation is carried out in the form of
mechatronic, hydraulic or hybrid solutions that initiate braking or turning manoeuvres in fractions of a second. It is claimed that they are at least as safe as conventional systems using mechanical transmission paths. A safety system with multiple redundancy ensures that correct sensor values are always transferred and processed.
Electronic steering not only promises increased driving comfort and precision for tractors and self-propelled harvesting machines, but also enables vehicle operation in critical situations without the need for a human in the cockpit. The driver exits the vehicle, activates the radio remote control and controls the vehicle from the exterior. This example shows that the farmer and driver will remain a team, although machines will operate autonomously on fields in the future. These technical capabilities have also arrived in other off-highway sector branches. While many agricultural machinery manufacturers are still in the project or pilot phase, particularly due to the lack of legal certainty surrounding autonomous driving in the public realm,
autonomous driving is already part of daily life in open-cast mining. In the massive raw material mines operated by Australian mining company Rio Tinto in Australia,
for example, autonomous Komatsu dumper trucks fitted with the Autonomous Haulage System (AHS) transport iron ore without a driver at the wheel. They find their way with the aid of high-precision GPS, while radar and laser sensors enable them to detect obstacles. Sensors for next-level autonomy Sensor systems are the sensory organs of mobile machines and are consequently also very high up on the technology providers' road map. The objective is maximum precision in person and object identification. The prerequisite for this is reliable 360-degree registration of the surrounding, often unstructured, terrain. The current sensor and camera technologies and the matching image processing algorithms now enable assistance systems that are adapted to customers' respective requirements and the type of mobile working machine.
In implementing this, the developers are not simply relying on one single sensor type: a complete model of the environment is only achieved by combining the information from various sensors (sensor fusion) – a fundamental prerequisite for the reliability and safety of driver assistance systems and autonomous driving. The use of LiDAR sensors (Light Detection And Ranging) is increasingly shifting into focus as a supplement to camera, radar and ultrasound technology. These sensors are aimed at helping autonomously operating working machines to achieve a breakthrough in the off-highway sector, and are considered by experts such as Aine Denari, Senior Vice President and General Manager of ZF's Electronics and Advanced Driver Assist Systems Division, to be one of the key technologies. The LiDAR systems register their environment on the basis of visible, ultraviolet or infrared light and generate a seamless 3D point cloud even in rain, fog, dust or darkness. The additional processing of GPS data makes real-time navigation even better in order to prevent possible collisions, thus enabling agricultural work such as sowing and the pinpoint application of fertiliser and crop protection agents to be extended into the night without any loss of precision. If the tractor is also able to obtain data from weather stations, it can determine when working conditions on the field are best.
Computing power for cloud connection So that the machines can undertake these processes, they have to process the data accordingly. Simple automation control systems quickly encounter their limits here. Only the significantly higher computing power of the latest high-end PCs and telematics units enables autonomous functions to be implemented for agricultural and construction machines.
Their high performance means that they are also suitable for machines that communicate directly with one another and send data to the cloud. While tractors, combine harvesters and forage harvesters were separate units in the past, machine-to-machine communication (M2M) will enable them to
autonomously exchange information such as their position, speed and loading capacity with one another in the future, thus optimising the harvesting and logistics process. This high processing capacity also enables precise coordination of multiple machines. Equipped with high-precision real-time kinematics and connected by means of a wireless data link, the vehicles exchange information about their position, speed and implement settings, enabling the implementation of an 'electronic drawbar', for example. This scenario, in which several machines process the field in a network, is called platooning. Another scenario is synchronisation with a drone.