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Artificial intelligence robots in everyday life 2022


Artificial intelligence robots in everyday life 2022

Artificial intelligence robots in everyday life 20.22

With the rapid development of artificial intelligence technology, it has become an era where we can easily meet artificial intelligence in various fields of life. Now, the machine listens to and responds to us (language interpretation and translation, speech recognition, utterance), identifies who the target is (face recognition, human recognition), distinguishes what kind of object it is (object recognition), and recognizes human emotions (emotion recognition). You can read or search for appropriate information, and you can make an appropriate recommendation that is specialized for you.

It has even become possible to compose music or imitate rare and famous works, and in some areas, it has surpassed human abilities, demonstrating victory over humans in battles like Go's AlphaGo and StarCraft's AlphaStar. It is showing that, with sufficient data and suitable learning algorithms, artificial intelligence that exceeds (or transcends) human intelligence is possible in certain areas.

If so, how far has the technological level of artificial intelligence robots that perform physical movements have advanced? Along with the rapid development of artificial intelligence, automated machines that used to repeat simple tasks at the production site and entertainment robots that were presented as a spectacle have recently evolved into smarter robots equipped with artificial intelligence. Artificial intelligence robots that we only dreamed of are appearing around us one by one.

In factories, the demand for automation is increasing due to the shortage of manpower at the production site and rising labor costs. It automatically assembles glass and tires, repeatedly transports heavy and dangerous objects, and sorts and picks up fast-moving products on conveyor belts. Sometimes, artificial intelligence robots that cooperate by assisting humans in production work have begun to replace humans for specific tasks in factories. The field of collaborative robots that collaborate with workers in the same field is also confirming the applicability.

In addition, as the demand for and interest in non-face-to-face physical services due to the COVID-19 pandemic increases, delivery robots, guide robots, and quarantine robots in restaurants have come into real life and started to coexist with people.

The current situation demands that robots become a necessity that constantly helps people in their daily life. In order to become an inconvenient existence like a smartphone or a car, and furthermore, it is expected to give practical help in life by thinking like a human, predicting, planning and acting like a person. However, contrary to our expectations, the reality is that the intelligence of robots is progressing slowly compared to artificial intelligence such as AlphaGo.

In this article, we will first define what robot artificial intelligence is, and look at what artificial intelligence robots will appear according to the definition. And find out which intelligent service robots are with us now. Finally, the technical requirements for future artificial intelligence robots are summarized, and the challenges to be considered when developing them are introduced.

Definition of artificial intelligence robot

In order to survive in various environments such as land, sea, forest, and underground, living things living in nature have sensory sensors for cognition, a body suitable for the environment, and physical abilities. It evolved by adapting to the environment with different appearances, such as animals with feet, fish with fins and gills, and birds with wings. Intelligence has also been specialized and developed with various natural intelligences to survive in each environment. Artificial intelligence robots, like living things, exist in physical space, so they can be defined from a similar point of view.

An artificial intelligence robot is “in the space (environment) where the robot works, it extracts the information necessary to achieve the desired task from the environmental (space) information obtained using the sensor mounted on the robot, and based on this, it performs optimized actions. It can be defined as “a robot that can learn, select, and create appropriately to perform a task without error”. According to this definition, the size and shape of the robot body will change according to the environment and target task for performing tasks, and sensors, actuators, and robot intelligence will also exist in different forms. Like natural organisms, artificial intelligence robots will be specialized according to the environment space in which the robot lives and the tasks to be performed, and will appear in various forms with different appearances and artificial intelligence.

The space in which robots live, and robots and intelligence that change in each space

Let's take a look at the space (environment) where the robot lives and what kind of work it is doing. The environment in which artificial intelligence robots live can be broadly divided into indoor and outdoor environments. In addition, the indoor and outdoor environments can be further subdivided into spaces with various characteristics. Outdoors, there are road spaces for autonomous vehicles to drive, large-scale residential complexes and urban spaces, agricultural spaces such as rice fields, fields and barns, construction spaces, sea and deep-sea spaces, drone flight zones, and disaster sites. Indoors, there is a factory space for producing, assembling, and manufacturing goods, a warehouse space for logistics, a commercial space such as an office, restaurant, and building interior used by the public, and a home space such as a house. Each space has a shape, structure, size, and various environmental factors, and the work required for each space is also different, and the specifications for the same type of work are also different.

For example, in the assembly process of a manufacturing line, picking up and assembling a connector with a size of cm and picking up and assembling a car glass or tire are the size, shape, sensor used, and required precision of the robot, respectively. , work hours, etc. are required differently. The size, force, shape, and size of the robot required for transporting objects weighing in tons with precision in millimeters and safely transporting food without spilling food with precision that can reach the destination within 10cm of the dining table table All sensors and specifications will be different.

Artificial intelligence robots are inevitably different. Nevertheless, we expect a robot of the same type (humanoid) with one technology or part to operate like a human with all functions. This expectation is a huge challenge. In reality, it is thought that specialized robots with artificial intelligence and shapes suitable for use by learning from natural intelligence will be commercialized first.

Artificial intelligence robots approaching everyday life

1) Mobile service robot

Autonomous transport and delivery service robots also have different robot intelligence for each space. In the factory space, delivery-logistics work that delivers and supplies various materials required for the assembly line is required, and continuous and repetitive logistics occur from the loading dock to the assembly line. Various robots are being applied to the field to automate this. In particular, since the main purpose of a factory is to increase the efficiency of product production, it can make a dedicated path for robots to travel, and does not care much about embedding devices in the floor or attaching additional devices in the factory.

Currently, the most used method is to guide the robot by attaching a magnetic tape to the floor. The tape is attached following the shape of the path the robot moves, and the robot moves in response to the magnetic field. When the robot's eye responds to a stimulus, it has a level of intelligence that generates a motion corresponding to that stimulus.

Another method is to closely attach a specific mark (QR code) to the floor (attached at a distance of less than 1m), read the QR code information, figure out where the robot is, and create a motion to go to the destination and move it. In this case, the robot has eyes to read the code on the floor. In addition, there is a method to determine the position by attaching a reflector around the main position where the robot moves and measuring the distance to multiple reflectors using a distance sensor mounted on the robot using a trigonometric method. Through this, it can be used like an indoor GPS.

This technology is being used well in assembly lines for mass production and in large distribution centers such as Amazon distribution centers. However, in the future, as the demand for small-lot production of various products increases, the assembly line will change frequently, and changes within the factory will also become more frequent. In each of these cases, it costs money and time to re-build all the infrastructure and attachments for the robot.

In order to replace these methods, a SLAM (Simultaneous Localization and Mapping) type robot is being tried as an alternative. In this method, the structure, pattern, and features in the factory are extracted and stored by themselves from the sensor (a technology that creates, memorizes and stores the map necessary for the robot to move by itself), and at the same time uses those features to determine the position of the robot (the robot's position in the created map). location-finding techniques). As the eye used here, a distance scan sensor such as LiDAR or a camera sensor to imitate a human eye is mainly used. This method has become mainstream in the last 10 years, and a lot of research and development has been done, and many mobile robot startup companies have appeared. Recently, it is changing to a sensor fusion method that maximizes the advantages of each sensor and complements the disadvantages.

Unlike factory spaces, in commercial spaces such as restaurants, large shopping malls and large buildings, it is difficult to install additional devices around the robot, and it is difficult to secure a path that only the robot moves. It is important to move.

Although a method for attaching a ceiling sign using a technology similar to that in a factory space is applied to some restaurant robots, the height of the ceiling is different for each store and it is difficult to recognize when exposed to direct sunlight, so it is not easy to apply it to various restaurants.

Most robots operated in commercial space adopt the slam method centered on the LiDAR sensor. Commercial space has severe structural and environmental changes within the space, and it is difficult to operate for a long time with a map once memorized.

Recently, autonomous driving and deep learning-based environmental recognition (recognition using object recognition from feature points) technologies to respond to these changes and operate robustly are being studied. In addition, research is being actively conducted in two ways: the method of transforming or updating the memorized map by adapting to changes in time and space, and the method of finding and remembering features that are not affected by the change. On the other hand, research on robot intelligence that enables safer driving by reinforcing learning of driving experiences in various driving environments to prevent collisions with humans is also being actively conducted.

In the home space, autonomous driving is possible based on the technology applied to the commercial space, but the problem is that there are various variables. Wheeled robots seem to have limitations in overcoming toys, carpets, steps and stairs on the floor. In addition, since the price of robots in a home environment must be absolutely cheaper than robots in factory and commercial spaces, robots for exchanging emotions that communicate with each other rather than aiming for a specific task are mainly used.

2) Collaborative service robot

Even robots (robot arms) that cooperatively perform tasks such as assembly, manipulation, and gripping in the same space as humans may have different robot intelligence in each space. In the factory space, the position of the industrial robot arm is fixed, and the work necessary for assembly is repeatedly performed by making the product in the exact same position and in the same posture on the assembly line. When a specific signal occurs, it has a level of intelligence that responds to the signal and repeats the same task. This robot is like an automated machine without eyes.

In recent factories, the assembly is carried out with partial autonomy by attaching eyes that can recognize two- and three-dimensional postures even when the position or posture of the product to be assembled is changed. A robot that automatically assembles automobile glass or tires automatically estimates the position and distortion of the vehicle body when the vehicle arrives, and precisely inserts the glass or wheel into the hole in mm to perform attachment and assembly work. Although it has partial autonomy, the robot is still fixedly working within a safety fence, and the robot and human do not share a workspace.

On the other hand, cobots, in which robots and humans share roles and collaborate, have emerged, and the number of cases that increase human work productivity is increasing. These robots must share a working space with people, and in order to safely assist in their work, various sensors instead of fences are controlled while observing the robot and the operator from the outside. It detects external contact by measuring the current of the robot's internal motor, or attaches a sensor that makes the robot feel tactile or measures proximity to an object to prevent collisions.

If you look at the latest trends in factory space, companies that supply industrial robots that moved quickly and precisely are making efforts to make industrial robots coexist with humans, and companies that manufacture cooperative robots replace the work of industrial robots with cooperative robots. are making an effort to As the intelligence of robots develops, the boundaries between industrial robots and collaborative robots are blurring, and the flexibility of robot tasks is increasing. In addition, in order to install an industrial robot, a jig/fixture is required that is 3 to 4 times the price of the robot. In order to make an autonomous robot without peripheral devices (JIG-Free), smart eyes must be installed and it will need to be transformed into an artificial intelligence robot that is combined with a mobile robot.

In commercial space, as food tech becomes a reality, automated cafes where AI robots cook or serve food and AI robots work are expanding. It is still possible to work at the level of repeating limited motions, such as grabbing a coffee cup and delivering it to a delivery robot or frying chicken in oil. However, it is expected to expand to more diverse fields. Research on home appliance robots to organize things in the home space or to automate cooking and laundry is also on the rise.

Development direction and challenges of artificial intelligence robots

1) Technical challenge

Although artificial intelligence technology is developing at the level of humans, can we say that the level of robot intelligence is sufficient to provide practical help by applying it to robots? It's hard to say I'm mature enough yet. OpenAI's recent language model, GPT-3 (Generation Pre-traination Transformer), has an intuitive ability to write text or even code. It is an artificial intelligence technology that is evaluated as a big step toward the goal of creating artificial general intelligence (AGI). GPT-3 is rated as one of the most likely candidates to pass the Turing test, and a whopping 175 billion parameters are generated by learning and used to infer.

Despite these reviews, they do not do everything well. I can only understand physics to the extent that I learned from texts, but I don't seem to understand the common sense of popular physics in the realm of time and space. As an input-to-output method that continuously predicts the next word based on a large amount of text data, it understands the state and goal of the robot (environment where the robot lives, work, etc.) in various variables of the real environment and understands the principle to make movement hard to bet It seems that artificial intelligence robots need to fully experience the world in real life using visual information and various cognitive sensors.

For example, consider a situation in which an artificial intelligence robot uses its arms to make coffee, put it in a cup, and deliver a cup of coffee to a customer using a mobile robot. The AI ​​robot needs to know that there are many variables such as how heavy the coffee cup is, how much coffee is contained, whether the surface of the cup is not slippery, how much force it can hold, and whether it can be lifted. It is possible to work only when each variable and various possibilities are modeled depending on some empirical data.

Humans have recorded thousands of years of experience in DNA with today's bodies and cognitive sensors. Alpha Star, an artificial intelligence that defeated humans in the strategy simulation game Starcraft 2, acquired the amount of game experience that a human must play for 10,000 years through simulation. It seems difficult for a robot to directly obtain such a vast amount of experience data, and in particular, data experienced by coexisting with humans is scarce. I think this is the reason why it is difficult to come up with an Alpha robot that responds to AlphaGo or AlphaStar.

In addition to robot intelligence to operate well on its own, artificial intelligence robots need social intelligence to coexist and cooperate with humans. Human-robot interaction requires intelligence that understands human intent. It is necessary to understand the content of the conversation to understand the person's explicit intention, or to minimize the uncertainty of the intention by continuing the conversation in case of unclear intention. In addition, it should be used to understand and sympathize with or interact with people's emotions, and in this case, it should be possible to properly understand the complex and subtle emotions of people.

It seems that cooperation between humans and artificial intelligence robots will be possible only when they can accurately understand and grasp human intentions and interact with appropriate social expressions. In other words, in order for artificial intelligence robots to coexist and collaborate with humans in real life, it is necessary to understand popular physics and public psychology. In addition, robot intelligence, sensor solutions, mechanisms, motors and control technologies are all important for AI robots to get smarter and do their jobs better.

2) Social and ethical challenges

As artificial intelligence develops, digital inequality will occur between countries and individuals depending on the level and gap of technology. Those who use artificial intelligence technology and artificial intelligence robots well can maximize convenience and efficiency, but inequality may occur beyond inconvenience to those who cannot use them. As the artificial intelligence and robot industries change rapidly, these social problems will come quickly, and we need to supplement the system and take policy measures.

In addition, it is necessary to respond to problems arising from abuse and abuse of artificial intelligence technology. Recently, deepfake technology that synthesizes human faces has become a big problem as it has been used for socially and ethically violating purposes. We must respond so that people are not harmed by the misuse of technology.

On the other hand, as the degree of freedom and autonomy of artificial intelligence robots increases, a situation in which the robot decides and acts on its own will occur. In this case, the robot should not retaliate against humans with emotions, and the robot itself should not injure people in order not to get hurt. Artificial intelligence that can say that it does not know what it does not know should be installed in the robot. To respond to this, explainable AI and artificial intelligence that can respond to uncertainty are needed. A black box that stores relevant data must be included so that the AI ​​robot can investigate and evaluate why it made such a decision.

concluding remarks

The emergence of artificial intelligence robots in real life will be an unavoidable path according to the needs of the public and the changing times in the demographic structure, rapid development of artificial intelligence technology, and the transition to a semi-compulsory non-face-to-face society due to COVID-19. If policies and systems to overcome technological challenges step by step and to solve social and ethical problems are supported, the transition to a future society in which humans and artificial intelligence robots coexist will take place in the near future.

In preparation for this, it is necessary for everyone to make efforts to enhance technological competitiveness internationally and maximize the positive impact of technology through steady discussions and responses to the technological, social, and ethical impacts of artificial intelligence robots.