AI with ROBOTICS
The word “robot” was used in science fiction play having the name Russell’s universal robot, which was written by the Karel Capek. A glimpse of the show is shown in the figure.
After this more development has started in the field of robotics. Today I will discuss robotics with AI. AI is an emerging branch similar to the robotics and if they combined together we can make more uses of both the field. As per the Robin Murphy stated in his book that, “Robots are good for the 3 D’s that includes jobs that are dirty, dull, or dangerous.” In the past, only the army and some of the industries only used the robots to fulfill their requirement but nowadays almost all the fields have started to include the robot. Some of the examples like space exploration, manufacturing unit, Agriculture where robots are used as an option of manual labor.
AI is the science to make machines intelligent similar to homo sapience(😁). AI got success from SIRI to self-driving cars. According to Robin Murphy, “The Handbook of Artificial Intelligence segregates the AI field into seven essential areas: Ability (knowledge) representation, perceiving natural language, training, outlining, diagnostic, inference, search, and vision.”
AI for robotics intelligence having three different partitions like autonomous, augmented, and assisted robotics intelligence.
There are two kinds of artificial intelligence:
Weak artificial intelligence: The computer is merely an instrument for investigating cognitive processes — the computer simulates intelligence. Strong artificial intelligence: The processes in the computer are intellectual, self-learning processes. Computers can ‘understand’ by means of the right software/programming and are able to optimize their own behavior on the basis of their former behavior and their experience.4 This includes automatic networking with other machines, which leads to a dramatic scaling effect.
Robots and intelligent machines can have not only supporting but even lifesaving functions. Examples are robots used in medical diagnostics, which have high accuracy, or for the assessment of dangerous objects using the remote control and integrated camera systems. These make it possible, for example, to defuse a bomb without a human having to come close to it. The ‘Robo Gas Inspector’, an inspection robot equipped with remote gas sensing technology, can inspect technical facilities even in hard-to-reach areas without putting humans at risk, for example, to detect leaks in above-ground and underground gas pipelines.
True and complete AI does not yet exist. At this level, AI will mimic human cognition to a point that it will enable the ability to dream, think, feel emotions, and have their own goals. Although there is no evidence yet this kind of true AI could exist before 2050, nevertheless the computer science principles driving AI forward, are rapidly advancing and it is important to assess its impact, not only from a technological standpoint but also from a social, ethical and legal perspective.
Another important application of AI in robotics is for the task of perception. Robots can sense the environment by means of integrated sensors or computer vision. In the last decade, computer systems have improved the quality of both sensing and vision. Perception is not only important for planning but also for creating an artificial sense of self-awareness in the robot. This permits supporting interactions with the robot with other entities in the same environment. This discipline is known as social robotics. It covers two broad domains: human-robot interactions (HCI) and cognitive robotics. The vision of HCI is to improve the robotic perception of humans such as in understanding activities, emotions, non-verbal communications, and in being able to navigate an environment along with humans. The field of cognitive robotics focuses on providing robots with the autonomous capacity of learning and acquiring knowledge from sophisticated levels of perception based on imitation and experience. It aims at mimicking the human cognitive system, which regulates the process of acquiring knowledge and understanding, through experience and sensorisation. In cognitive robotics, there are also models that incorporate motivation and curiosity to improve the quality and speed of knowledge acquisition through learning. AI has continued beating all records and overcoming many challenges that were unthinkable less than a decade ago. The combination of these advances will continue to reshape our understanding of robotic intelligence in many new domains.