What is the forward-looking and autonomous nature of internal logistics material handling tools?

In intralogistics, it primarily refers to the vehicle's ability to cope with unpredictable situations. This is fundamentally different from traditional automation requirements, which require devices to act independently in predictable situations.

You cannot change reality. Because the reality is that only about 5% of the warehouse space is built in the newly built hall, known as the "green space", where everything can be planned from the beginning to make the ideal adjustment according to the workflow. On the contrary, most warehouses are not "green fields", but "brownfields", that is, already existing situations, and new processes must be integrated into them. This has implications in terms of automation, for example.

Different industries, autonomy is also different

Automation is the future-and factory managers are convinced of it. Two years ago, a survey was conducted in which more than half of the customers said they would like to achieve "more than 60%" process automation by 2025, and about 1/4 even want to achieve full automation. This is an ambitious plan, especially considering that more than half of the respondents said they have not yet automated any process. However, these answers all emphasize the importance of these 1 topics to many people and what they hope to achieve.

Given people's expectations, the definition sometimes becomes blurred: what exactly is automation and autonomy, and what is the difference between the two? This question is not simple, because the answer actually depends on the application field. For example, in the automotive field, there is a standard to distinguish between levels, namely "the driver does not need to use his feet, the vehicle can accelerate and brake on its own" (level 2) or "the driver no longer needs to look at the road in certain areas" (Level 4). However, the challenges faced by autonomous robots in warehouses are completely different from vehicles on the road. To what extent can this level be meaningfully applied?

Centimeter-level navigation issues in the library

It includes ten functions that can be used to determine the degree of autonomy of an "automated guided vehicle"(AGV). Can it position itself independently in an open area? How well can it avoid obstacles? How accurately can it place goods on shelves? Here, the industry's role in defining autonomous driving is particularly obvious: in the case of autonomous vehicles, whether the vehicle follows the preceding vehicle at a consistently precise distance is secondary-the distance in road traffic is more relaxed. However, in the field of internal logistics, when the robot stands in front of the shelf to store or retrieve goods, its distance is often only a few centimeters, or even a few millimeters. On the other hand, it is essential for autonomous care robots to be able to communicate with people who need help. In the warehouse, communication with humans is a 1 additional gain, but not necessarily a prerequisite for autonomous action.

This is where the "brownfield" comes into play. In reality, warehouses are often walked around, pallets are not placed in the correct position, or other unpredictable situations are also part of daily life. In such an environment, the AGV's autonomy means that it can handle unpredictable situations in the most predictable and self-determining way. 1 intelligent autonomous software development director said: "intelligent robots can constantly perceive the surrounding environment, and adjust their behavior according to the perception results. It can work in different ways: the robot can react to unforeseen situations, for example, if there is an obstacle on the right, it will move to the left; if the space on the left is small, it will move to the right. It can even use all its knowledge to evaluate which behavior is best for the current situation and then make its own decision."

Automation and autonomy have their own strengths

This is also the decisive difference between autonomous driving and traditional automation: self-driving vehicles can accurately follow a predetermined route, but they cannot react to unexpected situations. The automatic storage equipment that travels in the warehouse according to the specified route is very suitable for the "new area" mentioned at the beginning: that is, in an environment suitable for vehicle use, the vehicle can process orders without interference and no accidents. In this ideal scenario, less autonomous vehicles would be even more efficient: This is precisely because autonomous vehicles have enough intelligence to leave the ideal route when encountering obstacles, thereby consuming time. "Customers can decide for themselves.

But at the same time, customers and manufacturers need to join forces to develop the most attractive applications. The automotive industry has a high number of units in the millions that can more easily incorporate new features into costs, while internal logistics relies on customers using their autonomous vehicles to create clear economic added value. Autonomous driving is no longer a distant future technology, but is already possible.