The modern business world involves various sector that is essential for the smooth and easy running of the company. An integral sector of the industrial world is the logistics of the products and resources. Logistics aims at avoiding any form of shortage and delay in delivering to the client any time. The industry must deliver goods and services with enough resources and technology. Proper logistics ensures an organized system of acquiring, storing, and transporting resources to the production unit along with collecting, storing, and delivering the finished product to the client. The current scenario in logistics is the shortage of efficient human labor to compete with the rising demand of the market. The use of human labor does not allow the industry to keep up with the ever-changing demand of the client. Market studies have shown that many logistics will run out of the required labor force in the next decade.
Industrial Robots
`Robot’ is a Czech word that stands for `forced labor.’ Most robots are designed and used for heavy or repetitive tasks that are boring for humans. A multipurpose robot that can be manipulated by programs and controlled to work in an industry is termed `Industrial Robot.’ The first `Industrial Robot’ was Unimate, which worked at an assembly line of General Motors at their New Jersey’s Inland Fisher Guide Plant. The six most common `Industrial Robots’ are Articulated, Cartesian, Cylindrical, Polar, SCARA, and Delta. Among these, the most flexible with six degrees of freedom and ideal for industrial use is the articulated robot. These are best suited for arc or spot welding, painting, ironing, material, and machine handling. Their precision, speed, and high endurance make it ideal for repetitive tasks like picking and placing, assembling, testing, and inspection of products.
AI-Powered Robot Pickers
The introduction of robots has greatly influenced the competitive area of logistics. Robots are replacing the human factor in the factory line, increasing the efficiency of the industry. The latest addition in the market of logistics and warehousing is the Robotic arms used as pickers running based on artificial intelligence.
Robots used to pick items are mobile and usually designed to retrieve and carry products autonomously in any warehouse and called `Picker Robots.’ These picker robots are programmed using `Artificial Intelligence’ or AI-powered software to identify the easiest way to pick, count, and return the items in a warehouse.
The use of AI pickers is growing in many warehouse facilities in Berlin and Germany. These AI pickers stack the goods considering various factors and parameters such as size, shape, and maximum goods stored, etc. They are used to reduce wastage of time, increase the speed, and efficiency of the industry. The AI picker contains an array of 6 lens camera that captures the images of the objects. These images are processed and converted to data that the AI programs as input data. A suitable surface is selected for the arm to pick up the object. The arm uses a suction method to pick and hold the object. However, it’s a challenge when the robotic arm is expected to pick and stack objects based on the shape and size. Programming such codes and commands that monitor every move of the robotic arm is tiresome. Machine Learning comes handy in overcoming this difficulty.
Machine learning works based on statistics and probability. The AI program feeds thousands of data points and the corresponding action on the object. Based on this data, a series of algorithms are used to predict the next move of the Robot, based on the statistical values and probability of the existing data given to the AI. The accuracy of the action of the robot increases as the number of data points given to the AI increases. The data points given to the AI trains, cross-validates, and tests the efficiency of the machine learning.
Machine learning is a training process and there are many methods to train the AI to obtain the desired action. The AI picker uses a technique known as reinforcement learning. It’s a trial and error-based training method where the AI gets rewarded for every correct action it performs and also punished for any incorrect action. To maximize the reward, it attempts to improve its learning. It also allows us to share the pattern with other AIs to train them and share the learning process.
Many MNCs have invested billions in understanding and developing AIs that would promote robotics in the manufacturing sector. Knapp, a German-based logistics company, has incorporated AI Pickers in the factory line with the help of Covariant, an AI and robotics startup from California. Other competitors in the market of the development of AI are Goggle and Facebook. Covariant has taken the market in the field of logistics by claiming that their product can function throughout the day with utmost accuracy. However, the loss of the human factor in the production and its effect on the unemployment rate due to poor working conditions and low salaries is high. The administration assures that these machines need supervision which will be by human touch.
