Artificial intelligence Index Introduction Content Artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. Since the development of the digital computer in the 1940s, it has been demonstrated that computers can be programmed to carry out very complex tasks, for example, discovering proofs for mathematical theorems or playing chess with great proficiency. Still, despite continuing advances in computer processing speed and memory capacity, there are as yet no programs that can match human flexibility over wider domains or in tasks requiring much everyday knowledge. On the other hand, some programs have attained the performance levels of human experts and professionals in performing certain specific tasks, so that artificial intelligence in this limited sense is found in applications as diverse as medical diagnosis, computer search engines, and voice or handwriting recognition. What is intelligence? All but the simplest human behaviour is ascribed to intelligence, while even the most complicated insect behaviour is never taken as an indication of intelligence. What is the difference? Consider the behaviour of the digger wasp, Sphex ichneumoneus. When the female wasp returns to her burrow with food, she first deposits it on the threshold, checks for intruders inside her burrow, and only then, if the coast is clear, carries her food inside. The real nature of the wasp’s instinctual behaviour is revealed if the food is moved a few inches away from the entrance to her burrow while she is inside: on emerging, she will repeat the whole procedure as often as the food is displaced. Intelligence conspicuously absent in the case of Sphex must include the ability to adapt to new circumstances. Psychologists generally do not characterize human intelligence by just one trait but by the combination of many diverse abilities. Research in AI has focused chiefly on the following components of intelligence: learning, reasoning, problem solving, perception, and using language. The Four Types of Artificial Intelligence Reactive Machines A reactive machine follows the most basic of AI principles and, as its name implies, is capable of only using its intelligence to perceive and react to the world in front of it. A reactive machine cannot store a memory and as a result cannot rely on past experiences to inform decision making in real-time. Perceiving the world directly means that reactive machines are designed to complete only a limited number of specialized duties. Intentionally narrowing a reactive machine’s worldview is not any sort of cost-cutting measure, however, and instead means that this type of AI will be more trustworthy and reliable — it will react the same way to the same stimuli every time. A famous example of a reactive machine is Deep Blue, which was designed by IBM in the 1990’s as a chess-playing supercomputer and defeated international grandmaster Gary Kasparov in a game. Deep Blue was only capable of identifying the pieces on a chess board and knowing how each moves based on the rules of chess, acknowledging each piece’s present position, and determining what the most logical move would be at that moment. The computer was not pursuing future potential moves by its opponent or trying to put its own pieces in better position. Every turn was viewed as its own reality, separate from any other movement that was made beforehand. Another example of a game-playing reactive machine is Google’s AlphaGo. AlphaGo is also incapable of evaluating future moves but relies on its own neural network to evaluate developments of the present game, giving it an edge over Deep Blue in a more complex game. AlphaGo also bested world-class competitors of the game, defeating champion Go player Lee Sedol in 2016. Though limited in scope and not easily altered, reactive machine artificial intelligence can attain a level of complexity, and offers reliability when created to fulfill repeatable tasks. Limited Memory Limited memory artificial intelligence has the ability to store previous data and predictions when gathering information and weighing potential decisions — essentially looking into the past for clues on what may come next. Limited memory artificial intelligence is more complex and presents greater possibilities than reactive machines. Limited memory AI is created when a team continuously trains a model in how to analyze and utilize new data or an AI environment is built so models can be automatically trained and renewed. When utilizing limited memory AI in machine learning, six steps must be followed: Training data must be created, the machine learning model must be created, the model must be able to make predictions, the model must be able to receive human or environmental feedback, that feedback must be stored as data, and these these steps must be reiterated as a cycle. There are three major machine learning models that utilize limited memory artificial intelligence: Reinforcement learning, which learns to make better predictions through repeated trial-and-error. Long Short Term Memory (LSTM), which utilizes past data to help predict the next item in a sequence. LTSMs view more recent information as most important when making predictions and discounts data from further in the past, though still utilizing it to form conclusions Evolutionary Generative Adversarial Networks (E-GAN), which evolves over time, growing to explore slightly modified paths based off of previous experiences with every new decision. This model is constantly in pursuit of a better path and utilizes simulations and statistics, or chance, to predict outcomes throughout its evolutionary mutation cycle. Theory of Mind Theory of Mind is just that theoretical. We have not yet achieved the technological and scientific capabilities necessary to reach this next level of artificial intelligence. The concept is based on the psychological premise of understanding that other living things have thoughts and emotions that affect the behavior of one’s self. In terms of AI machines, this would mean that AI could comprehend how humans, animals and other machines feel and make decisions through self-reflection and determination, and then will utilize that information to make decisions of their own. Essentially, machines would have to be able to grasp and process the concept of “mind,” the fluctuations of emotions in decision making and a litany of other psychological concepts in real time, creating a twoway relationship between people and artificial intelligence. Self-awareness Once Theory of Mind can be established in artificial intelligence, sometime well into the future, the final step will be for AI to become self-aware. This kind of artificial intelligence possesses human-level consciousness and understands its own existence in the world, as well as the presence and emotional state of others. It would be able to understand what others may need based on not just what they communicate to them but how they communicate it. Self-awareness in artificial intelligence relies both on human researchers understanding the premise of consciousness and then learning how to replicate that so it can be built into machines. Machine Learning & Deep Learning Much of Narrow AI is powered by breakthroughs in machine learning and deep learning. Understanding the difference between artificial intelligence, machine learning and deep learning can be confusing. Venture capitalist Frank Chen provides a good overview of how to distinguish between them, noting: Simply put, machine learning feeds a computer data and uses statistical techniques to help it "learn" how to get progressively better at a task, without having been specifically programmed for that task, eliminating the need for millions of lines of written code. Machine learning consists of both supervised learning (using labeled data sets) and unsupervised learning (using unlabeled data sets). Deep learning is a type of machine learning that runs inputs through a biologically-inspired neural network architecture. The neural networks contain a number of hidden layers through which the data is processed, allowing the machine to go "deep" in its learning, making connections and weighting input for the best results. What is a Drone? Outer space. Hurricane disaster zones. Antarctica. Your front door. One of these destinations is a little less extreme than the others, but that’s the point for drones. Drones, sometimes referred to as “Unmanned Aerial Vehicles” (UAVs) are meant to carry out tasks that range from the mundane to the ultra-dangerous. These robot-like vehicles can be found assisting the rescue of avalanche victims in the Swiss Alps, at your front doorstep dropping off your groceries and almost everywhere in between. Originally developed for the military and aerospace industries, drones have found their way into the mainstream because of the enhanced levels of safety and efficiency they bring. These robotic UAVs operate without a pilot on board and with different levels of autonomy. A drone’s autonomy level can range from remotely piloted (a human controls its movements) to advanced autonomy, which means that it relies on a system of sensors and LIDAR detectors to calculate its movement. Because drones can be controlled remotely and can be flown at varying distances and heights, they make perfect candidates to take on some of the toughest jobs in the world. They can be found assisting in a search for survivors after a hurricane, giving law enforcement and military an eye-in-the-sky during terrorist situations and advancing scientific research in some of the most extreme climates on the planet. Drones have even made their way into our homes and serve as entertainment for hobbyists and a vital tool for photographers. Drone Powered Inspections Monitoring Bridge Safety Safir Project Aims to Harmonize Rules for Drone Use in Europe Drones Spot Protected Bird Species in Tall Grass How do drones work? Unmanned Aerial Vehicles Drones are commonly referred to as Unmanned Aerial Vehicles (UAV)whereas the entire system that allows a drone to function is a UAS (Unmanned Aerial System.) The UAV is the heart of the UAS and possesses fixed wings or either a single or multi-rotary build for flight. Lighter-than-air UAVs, such as blimps and balloons, and small “Flapping Wing” UAVs also exist. Ground Control Station (GCS) Ground Control Stations are the central control unit that allows a UAV to fly and a UAS to operate. These stations can be as large as a desk with multiple views to as small as a handheld controller or even an app. The GCS can be user controlled or operated via satellites and is capable of controlling flight, controlling payload sensors, providing status readouts, mission planning and tethering the data link system. Payloads Drones, UAVs specifically, come in a variety of sizes and are capable of carrying payloads of equally variable sized payloads. From life saving medication to packages and more, drones provide an efficient method of delivery but must be built to handle the job at hand. Many drones are capable of rapid flight across oceans while others may be restricted to just a few thousand feet. Some drones may be capable of carrying hundreds of pounds while others can only manage under ten. It is crucial for operators to choose the right drone to help them complete the job at hand. Data Links Data Links act as the transmission center that allow the drone to communicate with the ground operator while in flight. Typically utilizing radio frequency technology to communicate, the data link provides the operator with crucial data like remaining flight time, distance from the operator, distance from target, airspeed altitude and more. Humans as Robots Humanoid robots are expected to exist and work in a close relationship with human beings in the everyday world and to serve the needs of physically handicapped people. These robots must be able to cope with the wide variety of tasks and objects encountered in dynamic unstructured environments. Humanoid robots for personal use for elderly and disabled people must be safe and easy to use. Therefore, humanoid robots need a lightweight body, high flexibility, many kinds of sensors and high intelligence. The successful introduction of these robots into human environments will rely on the development of human friendly components. The ideal end-effector for an artificial arm or a humanoid would be able to use the tools and objects that a person uses when working in the same environment. The modeling of a sophisticated hand is one of the challenges in the design of humanoid robots and artificial arms. A lot of research activities have been carried out to develop artificial robot hands with capabilities similar to the human hand. The hands require many actuators to be dexterously moved. However, the control system of the humanoid robot becomes more complicated if more actuators are additionally used for the hand design. This is a key aspect for the artificial arm because a handicapped person might not be able to control a complex hand mechanism with many actuators. For this reason, we propose to develop a lightweight hand driven by a single actuator. To this end we adopted a new mechanism for the cooperative movement of finger and palm joints. What is a mobil robot? A mobile robot is a machine controlled by software that use sensors and other technology to identify its surroundings and move around its environment. Mobile robots function using a combination of artificial intelligence (AI) and physical robotic elements, such as wheels, tracks and legs. Mobile robots are becoming increasingly popular across different business sectors. They are used to assist with work processes and even accomplish tasks that are impossible or dangerous for human workers. Mobile robotics is the specific industry related to creating these locomotive robot systems. Uses and functions of mobile robots The basic functions of a mobile robot include the ability to move and explore, transport payloads, or revenue producing cargo, and complete complex tasks using an onboard system, like robotic arms. While the industrial use of mobile robots is popular, especially in warehouses and distribution centers, its functions can also be applied to the medicine, surgery, personal assistance and security. Ocean and space exploration and navigation are also amongst the most common uses of mobile robots. Mobile robots are being used to access areas, such as nuclear power plants, where factors, like high radiation, make the area too dangerous for humans to inspect and monitor themselves. However, current mobile robotics is not designing robots that can tolerate high radiation without their electronic circuitry being impacted. Attempts to invent mobile robots to deal specifically with these situations are currently being made. Other uses of mobile robots include: shoreline exploration of mines; repairing ships; a robotic pack dog or exoskeleton to carry heavy loads for military troopers; painting and stripping machines or other structures; robotic arms to assist doctors in surgery; manufacturing automated prosthetics that imitate the body's natural functions and patrolling and monitoring applications, such as surveilling thermal and other environmental conditions. Advantages and disadvantages of mobile robots One major advantage of mobile robots is their computer vision capabilities. The complex array of sensors used by mobile robots to detect their surroundings allows them to accurately observe their environment in real time. This is valuable especially in industrial settings that are constantly changing and shifting. The onboard intelligence system and AI used by AMRs creates another advantage. The autonomy provided by the mobile robots' ability to learn their surroundings through either an uploaded blueprint or by driving around and developing a map, enables the quick adaption to new environments and assists in the continued pursuit of industrial productivity. Furthermore, mobile robots are flexible and quick to implement -since they can create their own pathways and easily adapt -- possible to break up the implementation into different installations with a modular deployment system and capable of removing the potential for human error by performing easily repeatable tasks, thus improving the safety of a facility or area. Disadvantages of mobile robots are the limitations on the size of the load that can be carried; requiring large amounts of SKUs to operate at the highest level and continued challenges with wireless connections between the robot and information endpoint. NASA and robots NASA tests robots for exploration in areas called analogs. Analogs are places where the environment is similar to locations like Mars or the moon, where a robot may be used. One NASA analog is in the Arizona desert. NASA robotics experts conduct field tests in the desert to assess new ideas for rovers, spacewalks and ground support. Some of these tests are conducted by a team called Desert RATS, which stands for Desert Research And Technology Studies. Curiosity is not your ordinary rover. It's bigger than a small car. The rover comes equipped "standard" with six-wheel rocker-bogie suspension and multiple camera systems, and its power supply doesn't rely on solar panels. Curiosity uses a radioisotope power generator so that it can roam longer and farther, traveling to more interesting places than previous missions. It has an expansive suite of science instruments named Sample Analysis at Mars, designed to analyze samples of material collected and delivered by the rover's arm. Why Do We Send Robots To Space? We can send robots to explore space without having to worry so much about their safety. Of course, we want these carefully built robots to last. We need them to stick around long enough to investigate and send us information about their destinations. But even if a robotic mission fails, the humans involved with the mission stay safe. Sending a robot to space is also much cheaper than sending a human. Robots don’t need to eat or sleep or go to the bathroom. They can survive in space for many years and can be left out there no need for a return trip! Plus, robots can do lots of things that humans can’t. Some can withstand harsh conditions, like extreme temperatures or high levels of radiation. Robots can also be built to do things that would be too risky or impossible for astronauts. Medical Robotics Surgical Robots Surgical robots refer to medical robots that are routinely used in surgery and used as medical equipment in integrated disciplines such as medicine, mechanics, biomechanics, and computer science. The existing surgical robots offer increased dexterity to surgeons. With the evolution of medical techniques and instrumentation, AI technologies such as computer vision technology, speech recognition technology, long-distance communication technology, and threedimensional imaging technology are gradually being incorporated into the surgical robot system. Surgical robots that have emerged over recent years have reached a high level of accuracy and feasibility in minimally invasive surgery but have aroused widespread concern in the academic community [40][41][42]. At present, the main characteristics of surgical robots are as follows: (a) Minimal invasion: The less invasive the surgical intervention, the greater the role of AI and the performance of specific tasks by medical robots [43]. Compared with traditional open surgery, one of the most significant advantages of surgical robots is fewer traumas, which can greatly reduce surgical wounds, shorten the recovery period of patients, and reduce the pain of patients. (b) High precision: Generally, surgical robots are provided to serve surgeons and patients. As one of the most prominent factors, the accuracy of surgical robots will directly affect the health and safety of humans. In the clinic, it is imperative that the safety and stability of the surgical robot can be guaranteed. Compared with traditional surgery, surgical robots have improved accuracy. (c) Wide range of surgical applications: due to the continuous optimization of driving and controlling manner, surgical robots are being selected by more and more departments in the hospital to perform surgical operations, resulting in an extensive increase of their application fields. (d) High sensitivity: As an important index affecting the working range, the sensitivity of medical robots is selected to characterize the working ability. By integrating sensors at proper positions, the sensitivity of surgical robots would be improved. Rehabilitation Robots Rehabilitation robots refer to the devices that can automatically perform tasks to replace or assist certain functions of the human body, thereby playing a role in the rehabilitation process. Rehabilitation robots currently play an important role in the functional reorganization and restoration, as well as metabolic compensation, of the nervous system, and the remission of muscle atrophy and joint atrophy. With the rapid expansion of intelligent control technology, network technology, simulation technology, and new material technology, the research and application of rehabilitation robots has increased the speed of the evolution process and accelerated the progress of related fields. Rehabilitation robots need to be modified and optimized constantly to better meet the needs of patients. Compared with traditional methods, rehabilitation robots can drive patients for rehabilitation training with several advantages as follows: (a) Single operation and strong repeatability: Rehabilitation robots (e.g., intelligent wheelchair, exoskeleton device, and training device) are often used to provide auxiliary services for disabled people. It is necessary for these processes to consume a large amount of time to execute simple and repetitive tasks and perform the set functions. Rehabilitation robots provide perfect training and service functions for strength, accuracy, and consistency in sports. (b) Personalized training: taking into consideration the severity of the injury and duration required for the recovery process, personalized training can be performed, and individual features, modes, and structures of rehabilitation robots are required. (c) High integration: A variety of sensors are usually integrated into rehabilitation robots with powerful information processing capabilities. By integrating sensors, kinematic and physiological data from patients can be recorded and measured during the process of rehabilitation training, and these data can be fed back to the robots in real-time so that the rehabilitation and training progress of patients can be quantitatively evaluated to provide the basis for surgeons to improve the treatment plan. Medical Assistant Robots Medical assistant robots are defined as robotic equipment, with patients as their service objects. They are used to substitute or support the hospital staff to perform medical transactions including examination, diagnosis, guidance, and disease analysis. The most prominent feature of medical assistant robots is that they replace nurses and physicians to provide diagnostic and treatment-related services to patients. Throughout the detection of disease and treatment, almost all operations related to medical procedures can be performed by medical assisted robots. Their use is not limited to hospitals, as they also have applications in daily life. At present, automatic medical diagnosis, monitor, health examinations, and other medical auxiliary work can be performed at home. Medical assistant robots have been used to assist medical staff, and in aspects of diagnosis and examination, automatic diagnosis robots are popular. As a symbol of technological progress, capsule robots have revolutionized diagnostic procedures in the gastrointestinal tract by minimizing discomfort and trauma. A capsule endoscope robot called NaviCam™ has been used in many medical examination centers. Previous research proposed a magnetically actuated soft robotic capsule robot to improve their diagnostic accuracy for submucosal tumors or diseases. Another study designed a novel capsule robot with the ability to move forward and backward, as well as turn, achieving the rendezvous and separation action through the three-dimensional rotating magnetic field. During the outbreak of COVID-19, some hospitals recognized the significance of robots. Medical assistant robots were used to provide hospital guidance, intelligent triage, automatic diagnosis, business consultation, and other services. With an increasing range of applications, the main characteristics of medical assistant robots used at medical institutions are reflected as follows: (a) Professionalization: To perform specific medical operations, such as disease diagnosis, prediction, parametric analysis, and inspection, medical assistant robots are equipped with expertise and endowed with high accuracy to perform specific procedures. This means medical assistance robots can be designed to perform purpose-specific tasks to achieve assistance in various medical environments. (b) Timeliness: During interactions with patients and doctors, it is necessary to quickly and accurately feedback the information required to improve the application experience. In the process of diagnosis and testing, a timely response can help patients and doctors get results as soon as possible, which reduces time costs, and means relevant treatment can be performed when necessary to avoid delays during illness. (c) A rich library of experts: With their high degree of AI technology, medical assistant robots can detect health parameters, diagnose diseases, and provide rationalized suggestions by detecting the biological characteristics of patients. These all require the support of a strong expert database to provide intelligent diagnosis and treatment programs. During the application process, the professional knowledge and experience of the robot are also constantly being optimized and enriched. Hospital Service Robots Hospital service robots are robotic devices used in hospitals or other medical institutions to provide services unrelated to medical operations. Controlled by a particular person in medical institutions, hospital service robots are used to carry out ancillary tasks unrelated to medical operations such as transportation, disinfection, transfer, and cleaning. The usage of hospital service robots greatly enhances the service quality for patients and reduces costs for medical institutions. The usage of hospital service robots can effectively relieve staff pressure and provide constant service on all days .Besides, hospital service robots also help patients to take medicines by delivering medicines and supplies only at the assigned location. The HelpMate, which was developed by the American Transportation Association, can transport food and medicine in hospitals. The TimRob , developed by Shanghai TimRob Technology Co. Ltd. (Shanghai, China), provides services in nuclear medicine wards such as propaganda and education, physical examination, radiation measurement, item distribution, remote video, and environmental monitoring, etc. Hospital service robots provide great assistance for medical staff and patients alike, and they generally have the following characteristics: (a) Anthropomorphic appearance: to improve interactions with humans, hospital service robots are mostly designed as anthropomorphic structures, on the assumption that an attractive appearance will be favored by the public. (b) Convenient movement: These robots must be developed to move in most scenarios while cleaning, disinfecting, transporting and transmitting. Flexible mobility is, therefore, a common characteristic of hospital service robots. Moreover, the easy-to-move feature can reduce the limitations of robot application scenarios. (c) Easy to operate: The simple and convenient operation method reduces the learning time and adaptation time of the operator, and it makes it easier to be promoted and applied. Both medical assistant robots and hospital service robots provide convenience to patients and medical staff. The significant difference between them lies in the usage purpose and the person who operates the robots. Medical assistant robots are used to provide auxiliary tools for medical processes, and the operators are professionals, such as surgeons and nurses in hospitals, or patients themselves. However, hospital service robots perform work unrelated to the medical process, and the operator is the specific staff member. Conclusion Bibliography Glossary
