The mobile robots or autonomous intelligent vehicles (AIV) are carving out a leading role in the logistics and production areas of many companies operating in different sectors and will be increasingly present. The reason is quickly explained: if used correctly, these means can lead to a net increase in efficiency in the warehouse, with the associated reduction of waste of time, and push productivity upwards.
Let's first clarify what is meant by the term mobile robot. In essence, we refer to small robots that can be equipped and configured in different ways, able to move independently within a defined area (for example, a logistics warehouse) and to transport loads and carry out a series of operations. The first feature that catches the eye of this type of robot is that of being able to move easily between shelves, production lines, forklifts, and so on. This allows you to use them to increase speed (can be close to 2 km / h) of performing the most repetitive actions that take place in these environments and to do it in total safety since the robots are able to identify obstacles and stop.
The task of mobile robots is very similar to that of the AGVs (Automatic guided vehicles): bringing material from one point to another. The way in which they operate is completely different. Instead of using existing infrastructures (cables, reflectors, etc.), all the sensors and route calculations are onboard the robot itself. The mobile robots, in fact, use the sensors mounted on board to detect the environment in which they operate. These sensors are usually laser scanners or cameras.
Typically when a mobile robot is put into service, it is taken "on a walk" with a joystick in the environment in which it will operate. During this phase, its sensors detect the planimetry. At the end of this phase, all the data detected by the sensors are processed to create the map of the entire surface. This procedure is of fundamental importance because it allows the robot to "learn" the environment and to move freely in it. Furthermore, it is very easy to learn different maps or modify existing maps in case of environmental changes. Due to its sensors and digital maps stored in the controller on the robot, the robot is, therefore, able to navigate freely in the environment, autonomously creating the routes avoiding any obstacles present during its motion.
Robots use different algorithms for localization and navigation. Typically algorithms called SLAM (Simultaneous Localization and Mapping) are used. The software recognizes the fundamental characteristics of the maps used to locate the vehicle. Detection of map highlights is normally used in combination with robot odometry generated by the use of wheel encoders and a series of gyroscopes and accelerometers in the robot itself. Mobile robots are also able to work in the presence of mobile obstacles, such as production personnel, thus being effectively enumerated among collaborative robots.
It is often mistaken to think that the use of robots is a substitute for workers' activities or, even worse, that robots will replace men by creating unemployment. In reality, robots must absolutely be used in collaboration with people's work. This allows workers to engage in activities that need their intellectual abilities more (which the robot does not have) and to contribute to the entire production or logistics process by collaborating with the robots and benefiting from the latter's help.
The world of logistics is certainly the one in which, so far, mobile robots have been mostly used. This is almost physiological if you consider the basic applications that the robot is able to perform. Specifically, autonomous intelligent vehicles are exploited in order fulfillment processes, in the transport of products, small pallets, containers from one place to another (for example, from a shelf to a loading bay). It is in these activities that, often, the main items of waste in the logistic environment traditionally lurk. The robot can identify the shortest path to complete in order to complete its mission and, if that route is not usable (for example, due to the presence of a machine), to immediately find the best alternative route possible. This also increases the productivity of men who can avoid wasting time and repetitive actions and dedicate themselves to the more complex activities of their work.
The activities of mobile robots are perfectly compatible also with those of the manufacturing companies. There are many sectors in which these vehicles have proved to be very useful, including automotive, digital, consumer goods, and many others. In these environments, the robots act as a bond between one line and another and between one production phase and another. For example, in the automotive sector, robots prove useful in mounting tires, transporting them from warehouses to vulcanizing presses, in the digital sector in moving semi-finished products, equipment, and tools to support workers, in transporting products along with the various production phases. Furthermore, these robots can be very useful even in catering and hospitality environments, where they are used for transporting baked food to warehouses or, in hotels, for room service and linen delivery.
Today, the production chains of industrial sites are flexible and dynamic. Various obstacles (operators, equipment, pallets) fill what were once free passages. The mobile robots adapt particularly well to these environments, and due to the collaborative and autonomous navigation, the automated transport of the materials are now flexible and easily adaptable without additional costs and disruptive processes, guaranteeing safety for the operations around the personnel.
The adoption of mobile robots in small and medium-sized enterprises has been relatively low until now, while large multinational companies have adopted our robots well in advance and are investing in ever larger fleets after a trial period of the different applications and after evaluating the economic advantages.
The trend we are witnessing today and which is the key to the mass adoption of robots will expand in the coming years. In particular, we will see how the man-robot collaboration will continue to develop and how the cobots at each level will be used effectively where repetitive or dangerous precision tasks are required while their human colleagues will be responsible for programming and quality control. The use of Artificial Intelligence in robotics will help robots to be increasingly sophisticated, intelligent, and responsive. The perception and applications of robots will increase dramatically when they can react to what they have learned. In the coming years, we will see the number of applications where there are mobile robots grow and how mobility will be combined with industrial robotic arms.