People often joke that robots will soon replace humans, even the most trivial daily tasks. We have seen many science fiction shows and movies, starting with Rossi, the maid of "Twilight" and "The Jasons". However, many robotics companies are replacing labor in a real arms race, especially in the supply chain.

However, when the numbers are calculated, it is usually still too expensive to implement, so manual is the most efficient and effective warehouse picking.

Industry reports estimate that warehouse picking accounts for 55% of operating center operating costs. Since warehouse picking directly affects customer satisfaction, business reputation and profitability, improving this activity is a top priority. The time it takes for employees to walk from one location to another is about 50% of the total picking time.

In addition, it is difficult to find and retain employees in today's tight labor market. This is usually a repetitive and costly recruitment and training cycle that results in them taking sick leave, failing to show up, or resigning within a few weeks or even days.

This means that facility managers and business owners must be careful when choosing picking strategies, which may affect efficiency. The size of the facility, the availability of financial and human resources, the number of SKUs in stock, and the number/frequency of demand are some of the factors that affect it.

It is difficult to see this situation and see no opportunity for robotics to reduce the burden. As the technology improves, it may even seem reasonable. The logical evolution of robot picking is a system that can perform fine operations, using arms and grippers to pick single items from the trash bin. Robotic engineers believe that fine manipulation is the next major breakthrough. The goal is to use machine vision and artificial intelligence to open a can of peanut butter or pick up a wine glass without breaking it that seems within reach.

In theory, a robot that can perform delicate operations like a picker will form a completely autonomous system that can correctly pick and pack a variety of items, regardless of their shape, size, weight or packaging design. But this is where things get complicated and expensive.

This is why the robotic technology used for warehouse picking is more complex than you might expect, and it is related to science. There is a well-known paradox in the field of artificial intelligence and robotics, which refers to the discovery that, contrary to your expectations, high-level reasoning requires relatively little computing power, while low-level sensorimotor skills require a lot of computing power. Calculate ability. In other words, things that are usually difficult for a person—such as winning a game of chess—are easy for a machine. What is easy for a person-taking a pen out of a drawer full of pencils-is quite complicated for the machine.

Although a few companies are developing sorting systems that have proven to be successful in picking individual items from handbags, there are still many problems when deploying such systems on a large scale. One is that most robotic arm systems are static. In order to pick goods for orders, suitcases need to be transported by shuttles, conveyor belts or other robots. This will almost certainly require the redesign of the warehouse or the construction of new facilities-a huge task in terms of time and cost.

Another problem is that the robotic arms currently working in factories use grippers designed to grasp specific objects to perform specialized tasks. Designing a gripper that can mimic the sensitivity and versatility of a human hand requires huge computing power, so most robotic picking arms use suction to grip objects, which usually limits the objects they can lift.

Consider the items you can order online: a box of washing powder, a can of kimchi, and a bag of rice. Although the size, shape, and weight vary, you can easily pick any of these items from the shelf with one hand. But for the robotic arm, not all of them can be accessed equally. The washing powder box is a thick cube, kimchi in a glass jar, and rice in a flexible bag. Develop an arm with a vision system and gripper that can correctly identify and pick up each of these items (and thousands of other items) every time, and the cost of construction, purchase and maintenance will be prohibitively high .

Although robotics may not seem to be the answer for the foreseeable future, there are better solutions. Minimizing the number of hands that the SKU passes through before shipment is a good way to increase productivity and efficiency. Companies should invest in hands-free equipment and technologies that promote warehouse automation. Although this brings upfront costs, the ROI of the initial investment is worth it.

Hiring a combination of human workers to pick together with automation, such as Autonomous Mobile Robots (AMR) working with them, is indeed the best choice. In the current labor shortage situation, using wearable technology and labor analysis to help coordinate people and machines, creating a more suitable solution for most organizations, as a way to achieve automation. In addition, many current wearable technology options provide voice picking and communication with modern warehouse automation and execution systems, which also help simplify the picking process.

Unfortunately, or fortunately, depending on how you look at it, the future of robots replacing humans in the supply chain is much further than we thought. Fortunately, there are several easy-to-use high-tech solutions to upgrade the warehouse picking experience.

Gabe Grifoni is the founder and CEO of Rufus Labs

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