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Why automated truck loading and unloading continues to be a challenge

Automated truck loading and unloading is the “Holy Grail” of intralogistics. Although many challenges have already been solved with automation, this particular task remains a difficult one. In the KION Group, we are working with advanced sensors and artificial intelligence to find a solution. Find out why humans and machines continue to work hand-in-hand and what progress has already been made.

2024-10-16

Johanna Wachner

The search for the “Holy Grail” has been a myth in both the western and the eastern world for centuries. According to legend, somewhere in the world is a chalice that promises eternal youth and happiness. Many have attempted to find this chalice, without success. The “Holy Grail” has become a synonym for a task that seemingly cannot be solved.

Our industry has its own “Holy Grail”: automated truck loading and unloading. A task that can be performed relatively quickly and easily with manual work. “Even an untrained worker can take it on after just three hours of training,” says Matthias Merz. “Automation has not yet fully succeeded, however, even though automatic loading systems have existed for decades.”

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The man who made this statement is far from an automation skeptic; as Senior Director Software Solutions at KION, Matthias Merz is personally driving forward the development of this technology. So why, of all things, is the task of automated truck loading and unloading so difficult to solve?

The answer is quite simple: the huge variance in the types of load and the unstructured environment of the loading docks require skill and problem-solving abilities that current automation simply does not possess. Humans are better able to adapt to unexpected changes in the arrangement of the load or the handling of fragile objects of different shapes and sizes than computer-controlled systems.

“The exact workflow may be very similar each time,” says Merz, “but it differs in small but significant ways.” There are indeed trucks and assistance systems that have recently been developed specifically for these applications and that significantly increase efficiency and safety, but it is still the case that “this task still needs to be performed by humans,” according to Merz, who continues, “and this is likely to remain so for some time.”

The solution is in sight

KION has long been looking for ways and means to overcome this challenge. Important aspects of this include innovative sensor technologies and improved cooperation between human and machine. By using sensors, automated guided vehicles (AGVs) are able to precisely perceive their environment – they gain their own eyes and ears, so to speak. This enables them to interact reactively and intelligently with their dynamic environment, supported by artificial intelligence (AI), cloud services, and 5G communication.

For Peter Krumbholz, Technology & Innovation Project Manager at KION, dynamic and even chaotic environments provide an “ideal testing ground” for autonomous systems. “Sensors enable automated devices to act quickly and safely, even in complex and unpredictable environments,” explains Krumbholz. Complete automation will be the next but one step. “We are currently witnessing the start of a real symbiosis between human and machine, in which both sides benefit from increased sensory perception,” says the expert.

The next step

The next level has long been in sight. Generative artificial intelligence (Gen AI), i.e., self-learning systems, will expand what is possible on a massive scale – KION automation expert Matthias Merz is convinced of this at least. “Within seconds, Gen AI can assess thousands of different possibilities as to how a system should proceed with a task,” he says. This will likely make the inconceivable conceivable.

Even if the “Holy Grail” has yet to be found, the KION Group is getting closer to the solution one step at a time. Sophisticated assistance systems are currently making the manual work of truck loading and unloading simpler, safer, and more convenient. And the question is no longer if this task can be fully automated, but when.