• Android Science:

    The development of robots that closely resemble human beings can contribute to cognitive research. An android provides an experimental apparatus that has the potential to be controlled more precisely than any human actor. However, preliminary results indicate that only very humanlike devices can elicit the broad range of responses that people typically direct toward each other.

  • Artificial Intelligence:

    Artificial intelligence (AI), deep learning, machine learning and neural networks represent incredibly exciting and powerful machine learning-based techniques used to solve many real-world problems. For a primer on machine learning, you may want to read this five-part series that I wrote. While human-like deductive reasoning, inference, and decision-making by a computer is still a long time away, there have been remarkable gains in the application of AI techniques and associated algorithms.

  • Nano-robots:

    Nano-robots are the robots that are simply known as that controllable machine at the nano (10-9) meter or molecular scale, composed of nano-components. More specifically, nano robotics refers to the still largely hypothetical nanotechnology engineering discipline of designing and building nano robots. Even though the field of nano robotics is fundamentally different from that of the macro robots due to the differences in scale and material, there are many similarities in design and control techniques that eventually could be projected and applied. Due to the modern scientific capabilities, it has become possible to attempt the creation of nano robotic devices and interface them with the macro world for control. There are countless such machines which exist in nature and there is an opportunity to build more of them by mimicking nature. Nowadays these nano robots play a vital role in the field of Bio Medicine. Especially in the treatment of cancer, Cerebral Aneurysm, kidney stones removal, also to remove the defected part in our DNA structure and some other treatments that has the greatest aid to save human lives. This paper guides to the recent research on nano robots in the Bio medical applications

  • Medical robotics:

    Medical robotics is an interdisciplinary field that focuses on developing electromechanical devices for clinical applications. The goal of this field is to enable new medical techniques by providing new capabilities to the physician or by providing assistance during surgical procedures. Medical robotics is a relatively young field, as the first recorded medical application occurred in 1985 for a brain biopsy. It has tremendous potential for improving the precision and capabilities of physicians when performing surgical procedures, and it is believed that the field will continue to grow as improved systems become available. This chapter offers a comprehensive overview about medical robotics field and its applications. It begins with an introduction to robotics, followed by a historical review of their use in medicine. Clinical applications in several different medical specialties are discusssed. The chapter concludes with a discussion of technology challenges and areas for future research.

  • Humanoid Robots:

    Human-oriented research on robotics is an active field. Researchers in the past tried to build robots that would mimic human beings and perform complicated tasks. Recently, they have shifted their main interest to human-symbiotic robotics in which human beings receive services from robots or are co-workers with robots in performing collaborative tasks. Hitachi began research on robotics at a very early stage and has been involved in many challenging projects since then. Its prototype intelligent robot in the 1970s and its Advanced Quadruped Robot in the 1980s are examples of Hitachi’s commitment to this field and the lessons learned from these projects are reflected in our latest EMIEW humanoid robots that act as evolving hubs between the human, machine, and information worlds

  • Robotic locomotion:

    Robotic locomotion systems serve as a base platform for much of the field of robotics. Although the general public notion of a robot usually conjures images of either walking bipeds or wheeled mobile robots, the types of systems developed in robotics research extend far beyond these two classes of robots. Starting from a very general definition of gait, one finds that it is quite natural to define a wide variety of machines and devices as qualifying as robotic locomotion systems, including swimming robots, satellites with rotors, and modular metamorphic robots.

  • Swarm robotics:

    Swarm robotics is a novel approach to the coordination of large numbers of robots and has emerged as the application of swarm intelligence to multi-robot systems. Different from other swarm intelligence studies, swarm robotics puts emphases on the physical embodiment of individuals and realistic interactions among the individuals and between the individuals and the environment. In this chapter, we present a brief review of this new approach. We first present its definition, discuss the main motivations behind the approach, as well as its distinguishing characteristics and major coordination mechanisms. Then we present a brief review of swarm robotics research along four axes; namely design, modelling and analysis, robots and problems.

  • Speech Processing :

    Automatic speech recognition (ASR) is an independent, machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speakerthrough a microphone, analyses it using some pattern, model, or algorithm, and produces an output, usually in the form of a text .It is important to distinguish speech recognition from speech understanding the latter being the process of determining the meaning of an utterance rather than its transcription. Speech recognition is also different from voice recognition: whereas speech recognition refers to the ability of a machine to recognize the words that are spoken voice recognition involves the ability of a machine to recognize speaking style


  • Image processing:

    Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. It is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image. Nowadays, image processing is among rapidly growing technologies. It forms core research area within engineering and computer science disciplines too.

    Image processing basically includes the following three steps:

    • Importing the image via image acquisition tools;
    • Analysing and manipulating the image;
    • Output in which result can be altered image or report that is based on image analysis.

  • Image processing:

    Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. It is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image. Nowadays, image processing is among rapidly growing technologies. It forms core research area within engineering and computer science disciplines too.

    Image processing basically includes the following three steps:

    • Importing the image via image acquisition tools;
    • Analysing and manipulating the image;
    • Output in which result can be altered image or report that is based on image analysis.

  • Cloud Robotics:

    With the development of cloud computing, big data, and other emerging technologies, the integration of cloud technology and multi-robot systems makes it possible to design multi-robot systems with improved energy efficiency, high real-time performance, and low cost. In order to address the potential of clouds in enhancing robotics for industrial systems, this paper describes the basic concepts and development process of cloud robotics and the overall architecture of these systems. Then, the major driving forces behind the development of cloud robotics are carefully analyzed from the point of view of cloud computing, big data, open source resources, robot cooperative learning, and network connectivity. Subsequently, the key issues and challenges in the current cloud robotic systems are proposed, and some possible solutions are also given. Finally, the potential value of cloud robotic systems in different practical applications is discussed.

  • Data mining:

    Data mining is the process of discovering meaningful new correlations, patterns and trends by sifting through large amounts of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques.

  • Underwater robotics:

    Underwater robotics applications have extensively grown in the last twenty years both for scientific investigations and industrial needs. Technological improvements in the design and development of the mechanics and electronics of the systems have been followed by the development of very efficient and elaborate control strategies. Indeed the framework of underwater robotics is challenging form both a theoretical and experimental point of view.

  • Ubiquitous Robotics:

    We present a concept of a ubiquitous industrial robot. It has been defined to consist of technologies of artificial intelligence, ubiquitous computing, sensor network and industrial robots. The advantages compared with current intelligent robots are that they are more autonomous and they have cognitive skills. A ubiquitous robot is interoperable with all sensors, computers and other devices around it. One important factor is the natural interaction with humans. The ubiquitous approach is more common in consumer applications but still new in the industrial environment, even if many research efforts are being made. We also present an example of a ubiquitous robot: the isle of automation.

  • Power System Control :

    A control system is a system of devices or set of devices, that manages, commands, directs or regulates the behaviour of other devices or systems to achieve desired results. In other words, the definition of a control system can be simplified as a system, which controls other systems. As the human civilization is being modernized day by day the demand for automation is increasing accordingly.

  • Agricultural Robot:

    Agriculture is the backbone of India. The robotics plays a major role in various fields such as industrial, medical, military applications etc., The robotics field are gradually increasing its productivity in agriculture field. Some of the major problems in the Indian agricultural are rising of input costs, availability of skilled labors, lack of water resources and crop monitoring. To overcome these problems, the automation technologies were used in agriculture. The automation in the agriculture could help farmers to reduce their efforts.The robots are being developed for the processes such as fruit picking, monitoring,irrigation, etc., All of these functions have not yet performed using a single robot.

  • Aerial Robotics:

    A wide array of potential applications exist for robots that have the level of mobility offered by flight. The military applications of aerial robotics have been recognized ever since the beginnings of powered flight, and they have already been realized to sometimes spectacular effect in surveillance, targeting, and even strike missions. The range of civilian applications is even greater and includes remote sensing, disaster response, image acquisition, surveillance, transportation, and delivery of goods

  • BEAM Robotics:


    BEAM robots are a type of robot that do not use computers. They are typically cheap to make and can be built within a few days—unlike computer-based robots that can be costly, complex and take years to build.BEAM robots can be either simple machines consisting of a solar cell, motor, transistors and capacitors or as complex as an 8-jointed, 4-legged walking spider machine.

  • Ant robotics:

    Ant robotics is a special case of swarm robotics. Swarm robots are simple (and hopefully, therefore cheap) robots with limited sensing and computational capabilities. This makes it feasible to deploy teams of swarm robots and take advantage of the resulting fault tolerance and parallelism. Swarm robots cannot use conventional planning methods due to their limited sensing and computational capabilities. Thus, their behaviour is often driven by local interactions. Ant robots are swarm robots that can communicate via markings, similar to ants that lay and follow pheromone trails. Some ant robots use long-lasting trails (either regular trails of a chemical substance or smart trails of transceivers. Others use short-lasting trails including heat and alcohol. Others even use virtual trails

  • Mechatronics:

    It is also called mechatronic engineering, or a department of engineering that concentrates on the engineering of both electrical and mechanical operations, and also includes a mixture of robotics, electronics, computer, telecommunications, systems, control, and product engineering. As technology develops over time, several subfields of engineering have resulted in both adapting and multiplying. The purpose of mechatronics is to offer a design clarification that unites each of these various subfields. Basically, the department of mechatronics was nothing more than a mixture of mechanics and electronics, hence the name is a portmanteau of mechanics and electronics; however, as the complexity of technical systems continued to evolve, the definition had been widened to include more technical areas.

  • Industrial Applications of Robotics

    Current innovation, for a dominant part of development, extends in creation, throwing, machining and get together offices, will be a significant supporter of ripeness development with ample gains in the assortment of products even with troublesome test and rivalry Industrial Robots have been being used for around 50 years. The Present-Day Robots at Work: Industrial Robots have come to assume a significant job in numerous modern systems today. These robots are quite often of the Jacquard type—with a couple of human qualities—as opposed to the doll-like structure. The work that robots can be grouped into three noteworthy divisions: in the gathering and completing of items; in the progression of materials and objects, and in the exhibition of work in naturally troublesome or risky conditions.

    Upcoming conferences: Robotics Conferences| Mechatronics Congress| Artificial Intelligence Conferences| Engineering Conferences| Deep Learning conferences |Industrial Engineering Meetings| Robotics and Automation Conferences

  •  Robotics: New Approaches in Automation

    In order to build autonomous robots that can complete helpful work in unstructured conditions, new methodologies have been created for structure wise frameworks. The relationship to customary scholarly apply autonomy and conventional computerized reasoning is analysed. In the new methodologies, a tight coupling of detecting to activity produces structures for knowledge that are systems of straightforward computational components which are very wide, yet not extremely profound. Ongoing work inside this methodology has exhibited the utilization of portrayals, desires, plans, objectives, and adapting, yet without falling back on the conventional employments of focal, conceptually manipulable or emblematic portrayals. The discernment inside these frameworks is frequently a functioning procedure, and the elements of the communications with the world are critical. The subject of how to assess and contrast the new with conventional work still incites incredible discourse.

    Mechatronics and System Engineering Conference | Mechatronics and System Engineering Workshop | Global Mechatronics Conference Mechatronics Symposium | Mechatronics and System Engineering Congress | Mechatronics and System Engineering Seminar | Annual Mechatronics Meeting | American Mechatronics and System Engineering Conference | European Mechatronics and System Engineering Conference | Asian Mechatronics and System Engineering Conference.

  • Data Science:

    There are many definitions for data science, but we like to think of the field as the multidisciplinary approach to unlocking stories and insights from the data being collected on a variety of behaviours, topics, and trends. Data science is everywhere — and chances are you’ve already interacted with it today a whole lot. Take Google’s search engine, for example. Its algorithm and site ranking and results are firmly in the realm of data science. If you’ve uploaded a photo on Facebook and the social media platform suggested tagging a friend, you’ve interacted with data science. That Netflix recommendation to continue your binge watching, Amazon’s product recommendations, or targeted advertisements are all the result of data science.

  • Deep Learning:

    Deep Learning is a machine learning technique that constructs artificial neural networks to mimic the structure and function of the human brain. In practice, deep learning, also known as deep structured learning or hierarchical learning, uses a large number hidden layers -typically more than 6 but often much higher - of nonlinear processing to extract features from data and transform the data into different levels of abstraction (representations).

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