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The Different Types Of Robots Used In Various Industries

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Question:

How Robotic Technology Could Be Incorporated Into The Future Operations?

 

Answer:

Introduction

Robotic technology management is the use of a robot which is a mechanical device that is programmable and is able to carry out tasks as well as have some interaction with the environment without the assistance of human beings. Therefore, robotics is the science and technology involved in the designing, manufacturing and usage of robots. This word robot was initially coined by Czech playwright Karel Capek in the year 1921 where he wrote a play and called it ‘Rossum’s Universal Robots’ which was all about a class of slaves working in the manufacturing industry and the struggle they went through to gain freedom. Therefore ‘robota’ simply meant ‘compulsive servitude’. The power to crunch all sensory data is growing enormously i.e. computers is shrinking in size but their capacity is growing. 

Perception is the most growing areas in the use of robots. Technologies such as laser scanners, machine vision, light 3D scanners etc and the soft wares related to mapping and imaging have made their way into more current technologies and this has opened great doors for robot experts. The science fiction writer Isaac Asimov was the first person to use the word robotics in the year 1941. Robots can learn more effectively and quickly. Various methods have been adapted for robot learning with some showing promising results in some research labs in the world. Robotic technology has been in existence for quite a very long time since its inception in the 19th century. However this technology has been advancing with time and there are current uses that cannot go unnoticed in this millennia. A robot is mainly composed of a body/frame, manipulators, control system and drive train.

 

Objective and methodology

Robotics technology has for a long time made doing business quite simplified and it’s a technology that is being adapted by many businesses worldwide so as to cut down on salaries as well as improve efficiency. The main objective of this report is to make a clear understanding of robotics, its current uses and have a deeper assessment of various uses of robotics in different industries. The report also aims at making proposal for future improvements in the adaption and use of robotics in the artificial intelligence field. Information in this report is therefore sourced from peer review articles and internet sources.

Report outline

The report starts off by first defining robotics technology, its current uses and then the application of robotics technology in various industries. The report then gives suggestions on how this technology can be better used in the future. It then concludes and makes some recommendations regarding robotics technology.

Current use of robotic technology

For instance in 2015/16 significance advancements have been made in both robotics and artificial intelligence.

China’s robot revolution

This is the world’s largest economy and it has recently embarked on great efforts in filling its many factories with current manufacturing robots (TRTWR, 2012). The government in this country has hopes that with this advancement it will be able to retain its wide range of manufacturing industry. This is because the workers’ wages have risen and manufacturing has become very efficient as well as advanced technologically management. Therefore the only way to keep up with global business completion china is opting to replace most of its workers with robots. This requires more advanced robots but cost efficient. The country is already investing heavily in robotics (Jormanainen and Sutinen, 2012). For instance, the country’s heartland i.e. the province of Guangdong has invested $ 154 billion in the installation of robots. The founder of Foxconn one of the leading technology companies in china promised to install more than 1 million robots in few years. Therefore, signs of whether this move of using robots in china will work or fail are huge expectations from other economies which may follow suit as soon as possible.

 

Smarter learning

Robots for so many years have only been effective for work that is precise and repetitive because they are believed to be so dumb. This explains why they have been used in settings that are carefully designed. Robots can also not adapt easily to new tasks and do not cope with situations that are unfamiliar. But thanks to the new technology because things are changing in regards to how robots operate. Articles such as ‘robot toddler learns to stand by imagining it’ and ‘robots learn to make pancakes from wiki how articles’ clearly indicate the progress that have been made in the advancement of robot technology (Sutherland et al., 2013).

There is an approach which seems to have a great impact in industrial robots. Robots have been trained to understand contents of audio, videos and images for deep learning that normally uses neural networks that are largely simulated (Blikstein, 2013). Some companies are working towards teaching robots to reason, grasp and see.

Knowledge sharing

This is where robots are now able to share the knowledge they have acquired with other robots. This speeds up the learning procedures by instantly allowing robots to get some benefits from the efforts made by others. Currently robots that are completely different from each other can comfortably teach each other on the recognition of some objects or carry out some task. Some projects are in the pipeline so as to provide good ways in which robots can combine their knowledge using the internet (Kantelhardt et al., 2013). This technology can be easily applied in industries where there is need to identify and grasp various objects.

Robots getting more personal

Some ‘personal’ robots were recently launched with a bit of disappointments from some prototypes. The successful one shave limited roles to play like the meeting and greeting of people in the stores within industries. However these robots need proper designing and programming for them to be effective when the social and emotional buttons are pressed (Mattei, 2013).

Droning on

Autonomous has finally taken off. The regulations for the registrations of drones were released in 2015 by the US federal aviation administration. This technology in robots will assist in the automatic air traffic controls and control of vehicles that are automatic (Eliza et al., 2012). This technology will be highly applicable in the industries that engage in automatic surveillance as well s inspections. It’s even projected that some holiday gifts will be delivered by robots through the air if the drones are well launched.

Different types of robots used in various industries and in different parts of the world

Case study- artificial intelligence, mining and transport industries

The advancement in the sensing technology has raised the IQ of robots to great new levels. The head start is provided by the sophisticated software’s as well as clever end-of-arm tooling. The tools of the future have been predicted to be EOAT and sensors software. Some faculties have been taken for granted and they include touch, taste, smell, sound and sight and these faculties are no longer exclusively associated with living creatures (Jimoyiannis, 2012). This is an indication that artificial intelligence has really gained ground. The current sensors are better, smaller, cheaper and very easy to integrate. There is therefore a lot of potential for robots coupled with technology in sensors.

Robot use in industries

Uncaliberated visual servings are used to replace the need for camera calibrations that are tedious. The motion of a robot is controlled by use of visual servoing (Goto et al., 2013). This has been achieved by the use of feedback signals from a vision system.  This technique can be used to do some tasks that are precise such as threading a needle. This is achieved by building a system that is able to do tracking which is reliable and the aim is to make it minimally calibrated. This application is being transitioned out of the laboratory to the commercial application. The founder of this technology says it has already been applied in some automotive factory in Paris. The CAD model of the object in use is used by the robot to perform its duties accurately (Demo et al., 2012). This is basically used for tracking purposes in the industries. Pierces have also been detected in bins and kitting applications have been achieved in this robotic technology. If such trays and kits can be built automatically instead of being done manually has interested many industries that deal in automotives, aerospace and electronics.  Bin picking was a challenge in robotics but it’s now easily approachable (L’Orsa et al., 2013). Some sensors include FANUC America Corporation’s 3D area sensor and Universal Robotics 3D sensing.  Mitsubishi Electric Automation and Nachi Robotic System have adopted this bin picking robot solution.

In terms of touch technology robots have also been used effectively and there has been a lot of advancements. Some of the applications include force feedback in the foundry. In this technology a force feedback hectic controller is used by an operator together with a force sensor in the operation of industrial robots that are of high-payload to play the role of a tele-manipulator (Heerink et al., 2012). This technology is used in the cleaning of some castings in foundries. Here all components are made in such a way that they can survive the severe environment once the functionality of the robot has been accessed and made to move in a plane the operator is able to have a feel of the forces that are placed on the work piece thus marinating a good pressure for cutting while removing risers from castings.

Robots technology has also been used in the sense of sound for the recognition of speech (Benitti, 2012). This is blooming in the consumer electronics industry for human robot interactions and collaboration. A robot has been developed in Georgia Tech where it’s given instructions for some food recipe and in collaboration with a human being they make some dish. The robot is simply told what should be done and it executes it (Adler, 2013).

For taste and smell senses robotics have not been left out. There are robots which can actually smell and taste things. Artificial intelligence has been used to mimic out senses by a researcher from Mexico. This has so far proved to be man’s best friend where electronic bloodhounds are part of the future for the robotics (Xiong et al., 2012). A chef robot has been designed from the use of 3D mappings of a chef preparing some recipes. For as long as the robot can cook people are ok with that and do not care whether it has a palate.

 



Currently the world is running on artificial intelligence for instance calendars are managed by Siri, friends suggested by face book and business stocks trended by computers. Some cars in the developed countries park themselves and air traffic is becoming almost fully automated. Almost all business fields have benefited in one way or another from artificial intelligence. This success is greatly attributed to the current use of robotic technology (Kandlhofer et al., 2012). However there are still more advances to be made in this sector and especially relating to the education industry. Artificial intelligence can take advantage of robotics technology to develop virtual mentors for learners. This involves the omnipresent support which has to integrate social simulation, user modeling and presentation of data (Bekelis et al., 2012). A robot can be developed where it educates and mentors learners without the tutor having to be present in class. This idea can also be of use in the medical industry in dealing with the treatment of some chronic disease. For instance robots can be developed to take part in the killing of cancerous cells in patients without necessary having the physical presence of the doctor around. They simply work on instructions (Schizas et al., 2012).

Robots should also be developed to address the 21st century skills where one can design a robot that is specifically meant to assist the learners with developing skills related to teamwork, self assessment and direction.  In learning people get to interact and share information on a vast number of issues. Robotics can be handy in analysis of such interaction data where specific robots are developed to assemble various types of data related to learning, social context, personal interests and learning contexts (Kubben and Pouratian, 2012). People across the world who share common interests and ideas are separated by geographical boundaries and robotics technology is one of the best ways to break this physical barrier to the sharing of knowledge and information. This is an advantage to countries that may not have some technologies in their schools but with such robots they are able to access quality learning materials from virtual classrooms. It’s been a tradition that learning has to be done in a school but with robotics lifelong and life wide technologies can be achieved where learning can be done outside the classrooms and objectives still be met. Some of these systems can actually outperform some of the untrained tutors in some topics. Robots can be designed to read, write and emulate the behavior of human beings (Litinas and Alimisis, 2013). A lot of understandings of robotics is related to the similarities between organic systems and robots however such an approach does not recognize the fact that human beings understands better how the robots work.

 

Conclusion

Robotics technology is advancement in the business world that has to be adapted by any business that aims at surviving in this competitive business world. This technology management saves on the amount of money spent on salaries and it also improves on work efficiency. However to invest in such technology requires a lot of cash investment and therefore companies should be ready to dig deeper into their pockets for such investments. Therefore a computational approach should be taken in the future use of robotics and educate pupils on a what stage they should leave computations to computers.  Robots can be designed to provide opportunities for creation of global classrooms. This will increase the interconnectedness as well as accessibility to classrooms globally.

All these strategies for the future of robotics technology should be implemented on either a short term or long term basis depending on their intended goals. For instance in the field of education these should be long term implementations but if it’s a manufacturing industry most implementations should be short term with aims of improvements in relation to competitions in the business world. With robots at work things like conflicts are minimized. However the robots have to be designed well for them to be efficient and effective and therefore their installment requires experts with much experience. There is still room for the improvements on robots for a better future and this should be embraced by all. High achieving robots are being created and are able to carry out human activities. This is due to the advancement in the tactile and force sensors, systems related to vision, recognition of speech and the advancement in the olfactory receptors.

Recommendations

Many companies should work towards investing in this technology

Robotics should be improved to accommodate future growth in business technology

A lot of keenness should be exercised in the designing of these robots for them to be effective in performing duties

The role of human beings at work places should not be entirely replaced by robots because they are still zombies and just as dumb as rocks.

 

References

Adler JR Jr (2013) The future of robotics in radiosurgery. Neurosurgery 72(Suppl 1):8–11.

Bekelis K, Radwan TA, Desai A, Roberts DW (2012) Frameless robotically targeted stereotactic brain biopsy: feasibility, diagnostic yield, and safety. J Neurosurg 116:1002–1006.

Benitti F.B.V. (2012). Exploring the educational potential of robotics in schools: a systematic review, Computers and Education, 58(3), 978–988.

Blikstein, P. (2013). Digital fabrication and ?making? in education: The democratization of invention. In J. Walter- Herrmann & C. B?ching (eds.), FabLabs: Of Machines, Makers and Inventors (pp. 1-21). Bielefeld: Transcript Publishers.

Demo, G. B., Moro, M., Pina, A., & Arlegui, A. (2012). In and out of the school activities implementing IBSE and  constructionist learning methodologies by means of robotics. In B. S. Barker, G. Nugent, N. Grandgenett & V. Adamchuk (eds.), Robots in K-12 education: A new technology for learning (pp. 66-92). Hershey PA: IGI Global.

Eliza M. Reynolds, Andre Grujovski, Tim Wright, Michael Foster, and H. Neal Reynolds (2012). Telemedicine and e-Health. 18(7): 507-515. doi:10.1089/tmj.2011.0206.

Goto T, Hongo K, Yako T, Hara Y, Okamoto J, Toyoda K, FujieMG, Iseki H (2013) The concept and feasibility of EXPERT: intelligent armrest using robotics technology. Neurosurgery 72(Suppl 1):39–42.

Heerink, M.  M. Daz Boladeras, J. Albo-Canals, C. Angulo Bahn (2012). A field study with primary school children on perception of social presence and interactive behavior with a pet robot, Proc. ROMAN.

Jimoyiannis, A. (2012). The new curriculum for Informatics Literacy in compulsory education: From design to  implementation. In T. Bratitsis (ed.), Proceedings of the 6th Pan-Hellenic Conference “Didactics of Informatics”  (p.15). Florina: HAICTE (in Greek).

Jormanainen, I., & Sutinen, E. (2012). Using data mining to support teacher's intervention in a robotics class.,  Proceedings of the 2012 IEEE Fourth International Conference on Digital Game and Intelligent Toy Enhanced Learning  (pp. 39-46). Washington, DC: IEEE.

Kandlhofer, M., Steinbauer, G., Sundström, P., & Weiss, A. (2012). Evaluating the long-term impact of  RoboCupJunior: A first investigation. In D. Obdrzalek (ed.), Proceedings of the 3rd International Conference on  Robotics in Education, RiE2012 (pp. 87-94). Prague: MatfyzPress.

Kantelhardt SR, FinkeM, Schweikard A, Giese A (2013) Evaluation of a completely robotized neurosurgical operating microscope. Neurosurgery 72(Suppl 1):19–26.

Kubben PL,  and Pouratian N (2012) An open-source and cross-platform framework for brain computer interface-guided robotic arm control. Surg Neurol Int 3:149.

L’Orsa R, Macnab CJ, Tavakoli M (2013) Introduction to haptics for neurosurgeons. Neurosurgery 72(Suppl 1):139–153

Litinas, A., & Alimisis, D. (2013). Planning, implementation and evaluation of lab activities using robotic technology management for teaching the phenomenon of motion. In A. Ladias, A. Mikropoulos, C. Panagiotakopoulos, F. Paraskeva, P. Pintelas, P. Politis, S. Retalis, D. Sampson, N. Fachantidis, & A. Chalkidis (eds.), Proceedings of the 3rd Pan-Hellenic Conference “Integration and Use of ICT in Educational Process”. Piraeus: HAICTE & University of Piraeus (in Greek).

Mattei T (2013) The O-Arm revolution in spine surgery. J Neurosurg Spine. 2013 Sep 20. [Epub ahead of print].

Schizas C, Thein E, Kwiatkowski B, Kulik G (2012) Pedicle screw insertion: robotic assistance versus conventional C-arm fluoroscopy. Acta Orthop Belg 78:240–245.

Sutherland GR, Lama S, Gan LS, Wolfsberger S, Zareinia K (2013) Merging machines with microsurgery: clinical experience with neuroArm. J Neurosurg 118:521–529

TRTWR (2012). International Workshop “Teaching Robotics, Teaching with Robotics”.

Xiong B, Ma L, Zhang C (2012). Robotic versus laparoscopic gastrectomy for gastric cancer: a meta-analysis of short outcomes. Surg Oncol; 21: 274–280.

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