Global Summit on Robotics and Artificial Intelligence August 18-19, 2022 Prague, Czech Republic

A mobile robot is a robot that is capable of moving in the surrounding (locomotion). Mobile robotics is usually considered to be a subfield of robotics and information engineering. A spying robot is an example of a mobile robot capable of movement in a given environment. Mobile robots have the capability to move around in their environment and are not fixed to one physical location. Mobile robots can be "autonomous" (AMR - autonomous mobile robot) which means they are capable of navigating an uncontrolled environment without the need for physical or electro-mechanical guidance devices.

Nano-robots remain in the realm of science fiction, though research efforts related to small-scale robotics are beginning to approach these dimensions. Nano robots are robots that are nano scale in size or large robots capable of manipulating objects that have dimensions in the nanoscale range with nano meter resolution. Nano robotic manipulation is an enabling technology for Nano electromechanical Systems or NEMS. NEMS with novel Nano scale materials and structures will enable many new nano sensors and nano actuators.

Micro robots are intelligent machines that operate at micron scales. Professor Brad Nelson and his colleagues at The Institute of Robotics and Intelligent Systems have recently demonstrated three distinct types of micro robots of progressively smaller size that are wirelessly powered and controlled by magnetic fields. These micron sized robots were fabricated and assembled by tools and processes developed by IRIS researchers. Many of these systems are used for robotic exploration within biological domains, such as in the investigation of molecular structures, cellular systems, and complex organism behaviour.

This paper deals with some intelligent control schemes for robotic systems, such as a hierarchical control based on fuzzy, neural network, genetic algorithm, reinforcement learning control, and group behavior control scheme. We also introduce the network robotic system, which is a new trend in robotic systems. The hierarchical control scheme has three levels: learning level, skill level and adaptation level. The learning level manipulates symbols to reason logically for control strategies. The skill level produces control references along with the control strategies and sensory information on environments. The adaptation level controls robots and machines while adapting to their environments which include uncertainties. For these levels and to connect them, artificial intelligence, neural networks, fuzzy logic, and genetic algorithms are applied to the hierarchical control system while integrating and synthesizing themselves. To be intelligent, the hierarchical control system learns various experiences both in a top-down manner and a bottom-up manner.

Humans are integrating with technology. Not in the future – now. With the emergence of custom prosthetics that make us stronger and faster, neural implants that change how our brains work, and new senses and abilities that you’ve never dreamed of having, it’s time to start imagining what a better version of you might look like. Four years later, despite warnings from the surgeon, he had neural interfaces implanted that allowed him to control a robotic arm on another continent and communicate, nervous system to nervous system, with his wife, Irena, via electrodes in her arm. Back then it was considered risky, even reckless. He went ahead anyway, creating a media circus as he demonstrated how the chip made him remotely traceable to a computer and allowed him to open the automated security doors at his University of Sheffield lab without touching them. Some call it Trans humanism. It’s not a philosophy cybernetics expert Kevin Warwick associates himself with, but he can’t deny he’s a cyborg… or was. Warwick had a 2.5cm-long radio frequency identification (RFID) chip implanted in his arm in 1998.

When most people hear the term artificial intelligence, the first thing they usually think of is robots. That's because big-budget films and novels weave stories about human-like machines that wreak havoc on Earth. But nothing could be further from the truth. Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the most simple to those that are even more complex. The goals of artificial intelligence include mimicking human cognitive activity. Researchers and developers in the field are making surprisingly rapid strides in mimicking activities such as learning, reasoning, and perception, to the extent that these can be concretely defined. Some believe that innovators may soon be able to develop systems that exceed the capacity of humans to learn or reason out any subject. But others remain skeptical because all cognitive activity is laced with value judgments that are subject to human experience.

In order to build autonomous robots that can carry out useful work in unstructured environments new approaches have been developed to building intelligent systems. The relationship to traditional academic robotics and traditional artificial intelligence is examined. In the new approaches a tight coupling of sensing to action produces architectures for intelligence that are networks of simple computational elements which are quite broad, but not very deep. Recent work within this approach has demonstrated the use of representations, expectations, plans, goals, and learning, but without resorting to the traditional uses of central, abstractly manipulable or symbolic representations. Perception within these systems is often an active process, and the dynamics of the interactions with the world are extremely important. The question of how to evaluate and compare the new to traditional work still provokes vigorous discussion.

The Internet of Things (IoT) describes the network of physical objects—“things”—that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet. These devices range from ordinary household objects to sophisticated industrial tools. With more than 7 billion connected IoT devices today, experts are expecting this number to grow to 10 billion by 2020 and 22 billion by 2025. Oracle has a network of device partners .Over the past few years, IoT has become one of the most important technologies of the 21st century. Now that we can connect everyday objects—kitchen appliances, cars, thermostats, baby monitors—to the internet via embedded devices, seamless communication is possible between people, processes, and things.

Block chain and Machine Learning (ML) have been making a lot of noise over the last couple of years, but not so much together. Made famous as the underlying technology behind Satoshi Nakamoto’s bitcoin, it has since grown to prove that it can do a whole lot more. As a distributed ledger, block chain can manage almost any type of transaction in existence. This is the primary reason behind its rapidly growing popularity and power. The block chain is designed specifically to accelerate and simplify the process of how transactions are recorded. This means that any type of asset can be transparently transacted using this completely decentralized system. The key difference here is the fact that there’s no involvement from intermediaries like the government, banks, or even technology companies. Instead, it’s a massive collaboration with some great code which significantly reduces settlement and clearing times to a matter of seconds.

Humanoids robots have been gaining popularity in India for quite some time now. Although the country is still catching up with the developments in artificial intelligence and robotics as compared to others, Indian start-ups, as well as the government, are working at a rapid pace to integrate new-age technologies. According to IFR research, robot sales in India increased by 27 percent to a new peak of 2,627 units in India — almost the same as in Thailand. Another survey claims that India ranks third in implementing robotic automation.

Intelligent mechatronics is a technology on how to give human psychology to mechanical system so that human and mechanical system could interact with each other. The interaction between human and mechanical/computer system is still asymmetrical, because mechanical/compute system cannot understand human psychology well, although  human  can  easily  understand the computer way of thinking. The goal of intelligent mechatronics is to achieve a symmetrical interaction between human and mechanical system. Intelligent mechatronics  is  a new discipline  based on the  integration of mechanical, electrical, information technology, human sciences including medicine, psychology, social science, and so forth. In this presentation, the past and present status of intelligent mechatronics is reviewed and the future  prospect is discussed.

Computer Vision, often abbreviated as CV, is defined as a field of study that seeks to develop techniques to help computers “see” and understand the content of digital images such as photographs and videos. The problem of computer vision appears simple because it is trivially solved by people, even very young children. Nevertheless, it largely remains an unsolved problem based both on the limited understanding of biological vision and because of the complexity of vision perception in a dynamic and nearly infinitely varying physical world.

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.

Robotics has been used for decades in the automotive industry, but many industries since have seen the benefits of robotic automation. The rule of thumb for what industrial tasks are best for robots is the "Three D's" rule:  Any task that is Dirty, Dull or Dangerous. Typical robotic applications are simple and repetitive tasks that require dedicated resources to perform. With recent advancements in machine vision, artificial intelligence, collaborative robotics and other technologies, robots are more capable than ever to perform complex tasks that typically require human-like recognition, judgement and dexterity.

Robotics for agriculture and forestry (A&F ) represents the ultimate application of one of our society’s latest and most advanced innovations to its most ancient and important industries. Over the course of history, mechanization and automation increased crop output several orders of magnitude, enabling a geometric growth in population and an increase in quality of life across the globe. Rapid population growth and rising incomes in developing countries, however, require ever larger amounts of A&F output. This chapter addresses robotics for A& F in the form of case studies where robotics is being successfully applied to solve well-identified problems. With respect to plant crops, the focus is on the in-field or in-farm tasks necessary to guarantee a quality crop and, generally speaking, end at harvest time. In the livestock domain, the focus is on breeding and nurturing, exploiting, harvesting, and slaughtering and processing. The chapter is organized in four main sections. The first one explains the scope, in particular, what aspects of robotics for A&F are dealt with in the chapter

A mobile robot is a robot that is capable of moving in the surrounding (locomotion). Mobile robotics is usually considered to be a subfield of robotics and information engineering. A spying robot is an example of a mobile robot capable of movement in a given environment. Mobile robots have the capability to move around in their environment and are not fixed to one physical location. Mobile robots can be "autonomous" (AMR - autonomous mobile robot) which means they are capable of navigating an uncontrolled environment without the need for physical or electro-mechanical guidance devices.