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The robots are coming

29 November, 2018

Robots are increasingly present in the workplace. They bring many benefits from doing the heavy lifting to performing repetitive tasks. But most of these robots are still static and are typically kept separate from human personnel working at the location. To fully integrate robots, and especially mobile robots in a collaborative environment, there are many challenges that need to be overcome.

Careful assessment

Building a manufacturing line requires careful analysis and assessment of the different steps to build an efficient and effective process. Adding robots into the equation requests a slightly different approach of the projects. The system needs to ensure that personnel can interact safely with the robots, ideally without impacting the efficiency of the production line. And if the robots are mobile, then careful planning needs to be made so they can safely navigate around the plant, avoiding personnel, other robots and machinery and any other obstacles.

Once an analysis has been completed, it is then possible to define and implement an architecture for the whole system. The default rules and routes that are defined in the architecture can then be parametrized into the robots to allow them to navigate their way around the plant. This is important for maintaining efficiency of the system as it allows them to operate independently of central control, for example if the wireless connection is temporarily broken or if the robot needs to react to unpredicted situations.

Smart robots

Whether static or mobile, robots need to be ‘smart’. But what does that mean? For a robot to be able to make intelligent decisions, it first needs to be aware of its surrounding environment.

That means it needs some sensors including cameras, lasers, radar, etc. For example, one early iteration of Omron’s mobile robots had a forward- looking LIDAR sensor for detecting objects in its path. This sensor scanned horizontally from left to right. However, it did not scan up and down with the unfortunate result that the robot could crash into or get stuck under objects with a ground clearance that was higher than the LIDAR sensor but lower than the height of the robot. This meant adding a second LIDAR sensor that also scanned up and down. But this also increased the complexity of the sensor network and the rules needed for navigating the robot around objects.

Just like the GPS systems in our cars, industrial robots use maps to find their way around. And just as there are accidents and traffic jams that can affect our commute, mobile robots also have to deal with obstacles or people in their path. To be able to navigate successfully on their own, robots need a clear map of their surroundings. They also need sensors to detect what is around them. If a robot sees that there is a blockage on its path, it can then use its map and sensors to maneuver safely around it.

For a static object this is a fairly simple task. But what happens if the other object is moving? Programming robots is probably the biggest challenge for production lines. Complex algorithms are needed to allow a robot to identify what it is ‘seeing’ and what to do in every possible scenario. And with increasing autonomy, the number of sensors and the software needed to safely control the robots becomes increasingly complex.

This increasing complexity requires increasing processing power which takes more of the robot’s battery capacity. At Omron, the processing systems in its first robots only accounted for about 10% of the robot’s battery life, but they were quite limited in what they could sense and do. Its latest robots are much smarter and more autonomous, but their processing accounts for 20%-25% of battery capacity. For comparison, the human brain also uses about 20%-30% of a person’s energy.

New ways in logistics

Autonomous transport systems like Omron’s LD robots not only have an impact on manufacturing but also on intralogistics. In fact, they foster the change from Pushed Flow Management to Pulled Flow Management with its advantages of smaller lots, lower inventories, and less waste. As most manufacturers in the industry try to go from a just-in-case to a just-in-time process, intelligent robots become a preferred means of achieving this change.

At present, Omron LD robots which carry a maximum payload of 130 kg already interact with forklifts who handle large and heavy palettes. Palette handling is still difficult for robots – for example they have to keep an eye on the center of gravity if a palette is imbalanced. That is why Omron is developing larger and even smarter robots for the warehouse, the Omron MD (Medium Duty) and Omron HD (Heavy Duty) models which can also handle huge payloads and thus will increasingly replace forklifts in the near future.

But even now, the advantages using transport robots in logistics are obvious: For example, a manufacturer of coffee capsules with many different varieties for black coffee, cappuccino, latte macchiato etc. combines different combinations of capsules for different countries – i.e. Italians having different preferences compared to Indians. With autonomous robots doing the compilation of the right capsules, the packaging process becomes easy and efficient.

Everything in its right place

One of the things that computers can do very well is to manage complex interactions. In a production environment, a fleet management system can effectively manage all the robots, assigning them to tasks based on an optimal planning that will for example charge some robots while the others are working, to ensure that there is always a fully charged robot available for tasks.

These advanced systems can even plan many steps ahead, like a chess program making a move that will set up a checkmate several moves later. So, it can assign tasks that may not seem logical to an operator. For example, it might not send the closest robot to perform a task because that robot is already assigned for another task or perhaps because the other robot needs to recharge after it delivers its load to a location that is near to the charging station. This type of advanced planning would be impossible for a human to manage, certainly when trying to control a whole fleet of robots, but with an advanced fleet management program it can bring additional efficiencies to production and manufacturing lines.

These systems can also draw on inputs from the individual robots. If a robot detects that a route is blocked, it can work out a new route and let the system know that there is a blockage. The fleet management system can then inform the rest of the robots about the blockage, so they also know to avoid it and which alternative route to use. But how does the system know when the blockage is cleared? Well, it will occasionally send one robot that way to check if the blockage is gone.

Let them take our job

Many people are worried that robots are going to take their job. For some tasks, that is actually a good thing. In one plant, it was determined that personnel were pushing trolleys up to 14 km per day. For physically demanding manual labor like this, we should be happy that robots are coming to do the heavy lifting.

Robots can also ideal for use in hazardous environments. In the automotive sector, for example, cars are now almost exclusively painted by robots, a repetitive and hazardous task which used to be done by hand. And if you think about it, we have been replacing manual labor with machines since the dawn of the industrial age. When was the last time you went down the local river to scrub your clothes? Or did you just pop them into your washing machine?

So, let the robots handle the repetitive, heavy and dangerous tasks. It frees us up to do more valuable and interesting tasks that they cannot.

By Bruno Adam, Omron Mobile Robots Europe General Manager

Read more about Omron’s robotic solutions here.

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