The future of robotics

Subject: Technology
Type: Evaluation Essay
Pages: 3
Word count: 860
Topics: Robot, Artificial Intelligence, Automotive, Innovation

Forecasting is a word that has been widely used in business, research, and technology. Despite the wide range of meaning attached to the term, forecasting is generally used to refer to a technique for estimating the future of an occurrence. Although there are many types of forecasting that are used in various fields, the intent of every method is to help the forecaster predict the future. The rapid change in technology is a mighty force that has affected individuals, organizations, and government. To some extent, some people are afraid of investing in a technology due to such uncertainties (Hsu, 2003). Therefore, forecasting in technology can be used to identify disruptive technologies and thus can save an organization from investing in a technology that will affect them negatively later. However, it is hard to predict whether a technology is disruptive given that technological innovations come from different sectors. The intent of this essay is to present a forecast on robotics technology (Pearson, 2011). The paper outlines the basics of robotics technology, its use, and a prediction of how the technology is likely to change in the future.

Robotics is a complex technology that uses knowledge derived from engineering and computer science. The intent of robotics technology is to develop automated machines that replicate human operations. With the use advanced technologies in computer systems, robotics technology has rapidly grown to be used in various operations. For instance, robots have been used to work in dangerous areas that humans cannot survive like bomb detection and deactivation. With the development of internet of things and smart environment, there is a possibility that robotics technology will rapidly grow in the new future. To be able to effectively predict the future of robotics, we need to analyze the history of robotics and analyze the current trends in robotics.

The history of robotics can be attributed to the classical era where the invention of machines started. Although the classical machines were mechanical, use of robots did not start until early 20th century. Development of robotics is based on three primary laws: the presence of human-like arms, strict adherence to human instructions, and personal protection. Using these basic rules, technologists have been able to develop robots that can be used in various such as military, manufacturing plants, health, and domestic. Robots have been widely used in industries due to their precision and ability to work without fatigue like human beings. Due to the advantages associated with robotics, developed countries have greatly invested in filing their factories and processing plants with robots. For instance, China fills that adoption of robotics will help sustain her vast manufacturing sector. Use of robotics is consoling for many industries in terms of operational cost reduction given that wage bill is constantly on the rise.

Precision and ability to carry out repetitive work is the primary reason behind the vast growth of robotics technology. Although most robots use computer programs that that are passive, technologists believe that latest technologies can be used to develop smart robots. Using artificial intelligence, technologists are able to develop algorithms that can be used to make robots smarter and work effectively. Although there are different ways that can be used to make robots smart, it is evident that use of the neural network in artificial intelligence is the future of robotics. Using simulated neural networks, technologists have been able to efficiently and effective train machines to recognize media content such as voice, images, and videos.

With the growth of internet of things, big data, and cloud computing technologies, we can be able to predict a bright future of robotics technology. Use of internet data sharing among robots can be effectively used to implement smart environment such as smart cities. Additionally, connected robots can be used to handle changing activities in industries. Due to these technologies, the line between artificial intelligence, robotics, and biological environment is blurring. With the current robotics trend, it is possible to predict that robots of the future will be smart enough to communicate to each other, monitor, and repair natural environmental problems. For instance, nano-robots will be used in the treatment of cancer (Knight, 2016).

Additionally, current research is geared towards the development of robots that are beyond the current standards. In addition to having robots that have the mechanical, electrical, and computational capability, research is underway to come up with robots that have body, brain, and stomach. This is a confirmation that robots of the future with have more than biological functionalities. Researchers are working on developing soft robotics that are environmentally safe and can be integrated with biological tissue. Results of this research are having a class of robots that will not have an adverse effect on the environment as they will be able to live, die, and decompose without environmental degradation (Rossiter, 2017).

In conclusion, it is rightful to say that the future of robotics is not with us yet. With the current change in technology, it is impossible to correctly predict the future of robotics technology. Just like it was impossible to predict the impact of the internet thirty years ago, it is entirely impossible to predict the future of robotics.

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  1. Hsu, P. H. (2003). A Litterman BVAR approach for production forecasting of technology industries. Technological Forecasting and Social Change, 70(1), 67-82.
  2. Knight, W. (2016, January 1). 5 Robot Trends to Watch for in 2016. Retrieved from MIT Technology review:
  3. Pearson, R. L. (2011). Forecasting Future Technology. INTERNATIONAL JOURNAL OF APPLIED, (20).
  4. Rossiter, J. (2017, April 6). Robotics, Smart Materials, and their Future Impact for Humans. Retrieved from MIT Technology Review:
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