Introduction:-
Distance education and online study are playing a growing role in modern education in this digital era. Conversely, engineering and science courses are more inspiring since they generally need laboratory and fieldwork machinery and hands-on involvement for learners to earn the full course recognition (Korn et al., 2018). Artificial Intelligence is a division of computer science that targets to instill software with the capability to examine its atmosphere using either prearranged instructions and search processes or pattern distinguishing machine learning prototypes. Intelligent robotics is a very optimistic gift of modern technology. In this research paper, the researcher tries to make a smart robotic lab with the help of the AI concept.
Overview:-
With the quick expansion of Artificial Intelligence, the human being want smoother testing facilities. The AI-empowered Robotic Testing Lab assimilates visual recognition, deep learning, data collection, automation, and exploration to deliver consumers personalized smart testing facilities. In this research paper, the researcher will deliver a literature review surveyed by the projected solution of AI-based Robot Empowered Smart Lab and its coordinating architecture with a thorough description of every section of the system (Namdev & Pandagre, 2014). AI robotic analysis incorporates Arduino cars, robotic arms, and visual recognition structure to certify the tests are directed in a reliable and reproducible method. Thus, adjusting the variables in investigations so that testing quality becomes more established, time efficiency can be augmented. Precise key quality threat issues can be replicated.
Figure: – Smart learning environment
Source: – (Tan et al., 2019)
Robotics has empowered significant rearrangement of the workstation. Many parts conventionally earmarked for ‘wet lab’ bench work have been transferred to handling robots proficient in the application of customizable and pre-programmed procedures. Technological competencies are repeatedly developing, basically impacting the way investigation is conducted. Cloud computing has prepared cooperation easier than ever before. The necessity for more effective data management systems has converted into a flow in the progress of AI solutions. The automation and robotics have carried great assistances in manufacturing; enlightening quantity and quality, and decreasing charge. The capability of laboratory robots to achieve fluid control has been a surprising success. It has permitted the high-throughput displays that would just not have been conceivable using physical pipetting. In the experimental laboratory, routine blood checks have reached a lesser price thanks to the automation application.
However, robotics structures have been valuable tools in the laboratory for several years, particularly in the range of liquid handling. Many jobs are still only computerized to a minor extent. At a similar time, an innovative wave of robotic tool (Ai based Robotic system) is launching the market, which is essential for business, education and manufacturing purposes. This assistance from the modern developments in sensors, mechatronics, and AI algorithms. Many of these improvements are essential for determining public finance programs (Vernon, 2019). This research paper highlights particular of the latest improvements in robotics, which have the prospective to take laboratory computerization, and the science it empowers, to the subsequent level.
Figure: – AI based Robotic Architecture
Source:- (“Robot Architectures”, 2020)
Research Questions:-
Selecting a research question is an important component of both qualitative and quantitative research. In this research paper, the researcher defines some specific research questions that should be vital for investigation. The questions are as follows-
How is AI used in robotics?
What are the distributional effects of AI and robotics?
What are the implications of robotics Smart Labs by AI?
Backup research Questions:-
What is the advantage of smart robotic lab for the student?
Why AI is important for using the smart robotic lab?
What is the drawback of AI based robot empowered smart Lab?
Literature Review:-
In the current time, many researchers are researching separately in Robotics and AI, but this research is a little bit different. By the way, some researchers also define their perception about AI-based robotic lab systems and, in this section, are defining there findings and outcomes. The upcoming robotics structure will be more social, cooperating securely with users. According to the research of Zawieska & Duffy (2014), the skills from other parts of robotics will be cheaper and more effective. Besides, the innovative robot will interconnect better with operators and users. Another researcher Bekiroglu et al., (2017) states that the robotic designed to be proficient in obvious social communication with persons necessitates engaging the mortal frame of orientation to a positive extent.
Conversely, there is similarly a fear that once this man-machine edge is overlapped that mechanisms will root the destruction of manhood. The idea recognized with the motto of “Making an eco-system where students become stimulated by automation and robotic technology, absorb technology and get revelation to global competitions. The research de Lima et al., (2016) have subjugated short term instructional sequences, and now they are prepared to look outside it. AI has played a very foremost role not only in growing the relaxations of humans but also by increasing manufacturing productivity, which contains the qualitative as well as quantitative production and budget-efficiency.
According to the research of Ting et al., (2018), AI is a computer platform that mostly emphasizes the progress and investigation of algorithms, which in other terms means that AI is a computer algorithm that is proficient in making a machine having its intelligence and performance. AI provides robots a computer vision to direct, calculate and sense their reaction consequently. Robots learn to implement their tasks from individuals through machine learning that is a portion of computer language and Artificial intelligence. The research Zawieska & Duffy (2015) states that AI is a universal term that suggests applying a processor to model or replicate the intelligent performance. A study in AI emphasizes the progress and investigation of algorithms that study or perform intelligent conduct with negligible human involvement. Robotic labs are essential for all students, and the AI-based robotic labs are not taking any human help.
This research also describes that the Experimental Robotics Lab aids the strategy, investigation, and execution of new robots with testing approaches that are severe and reproducible. Long-term objectives include constructing prosthetic devices reasonable to all who want them, growing the efficacy and security of building structure and lowering blocks to robots’ application for manufacturing computerization by small industries. Without AI-based programming, these kinds of facilities are not delivered by the smart robotic labs.
In the research of Gómez-Chabla et al., (2017) defines the advantages of AI-based laboratory robotics. According to the research the benefit includes high rapidity, high proficiency, negligible wastage, task reproducibility, task resolution, accuracy, high efficiency, and enhanced security for laboratory employees, the capability to survive adverse conservational circumstances, and reduced monotony and boredom among laboratory employees who would else perform the jobs.
This investigation needs cross-disciplinary surveys in some areas like biologically stimulated algorithms, evolutionary processes, cloud intelligence, machine learning, psychology, data mining, cognitive science and computational neuroscience. In the research of Pramanik et al. (2018), the researcher wants to design a tactic to combine software, hardware, and curriculum progress. The existing method is very beneficial. Whenever reducing charges is a primary objective because more than a few student groups can progress AI-based robot code instantaneously, applying simulation, and then trial the robot program in a prototype that can be distributed by several learners.
Methodology:-
The AI-based robotic lab prototype involves a three dimensional printed segment that applies reasonable hardware, such as an Arduino Uno platform. An AI-based robotic lab system upkeeps the whole planning procedure with the following purposes:
Development of planning quality,
The discount of planning charges,
Development of the range of solutions to be capable of creating the best choices,
Rise in imaginative planning,
Fast handling and research of planning documents,
Development of data flow,
Improvement of the transparency of scheduling,
Founding for robot combined CIM classifications,
For the projected robot, incessant rotation is necessary, so the AI program must be modified. This variation contains in separating the site potentiometer from the gear train, situating the potentiometer for an identified modulated signal and eliminating the angle stopovers from the shaft motor. In order to find the actuator prototype was compulsory to know for every control signal the output speed of every modified AI code incremental encoders were applied for that purpose. Such AI structures can become exceptionally effective in their field but lack generality ability. Most prevailing intelligent systems apply robotic lab as well as data mining, language processing and pattern identification. These procedures are controlled by human-like intellectual capacities counting cognizance, and self-awareness. Efforts proposing to produce a durable AI have dedicated to complete robotic brain replications.
The robotic lab is one dynamic field in artificial intelligence. It contains mechanical, frequently computer-monitored, devices to execute tasks that involve extreme accuracy or tedious or risky work by persons (Yao et al., 2017). Outdated Robotics applies AI planning methods to program robotic behaviors and works to robots as technical tools that have to be established and measured by a human engineer. The Autonomous Robotics lab method proposes that robots could improve and control themselves separately. These AI-based robotic labs are capable of adjusting to both inexact and incomplete evidence in continuously changing atmospheres. These are likely by imitating the learning procedure of a solitary natural creature or over Evolutionary Robotics, which is to relate discriminating imitation on populations of robots. It lets a replicated evolution procedure develop adaptive robots.
Figure: – AI for robotic Smart Lab
Source: – (Inc., 2020)
AI dramatically decreases or removes the threat to humans in several applications. Prevailing AI software supports to improve the high-precision machine abilities of robots fully, often releasing them from straight human control and massively enlightening their efficiency. When a robot interrelates with an elaborately occupied and variable world, it uses its senses to collect information and then relate the sensate inputs with fixed opportunities in its universal model. Therefore, the robot’s efficacy is inadequate by the precision to which its AI programming models the actual world. The standards for artificial structures contain the following:
1) Functional: The system needs to be proficient of performing the function for which it has been calculated;
2) Able to creation: The coordination must be proficient of being industrial by existing developed methods;
3) Designable: The system design must be thinkable by designers working in their cultural background;
4) Marketable: The system must be professed to aid some determination well adequate, when associated with competing methods, to permit its design and construction.
Data Collection:-
The information has been defined as an important tool for an extension. When information is inspected, counted, reviewed, exposed conditions and circumstances or statistically available, data are adequately arranged. Data dropped in columns are the characterized database (Jarrahi, 2018). Most of the documents are collected over several researcher articles and the AI-based robotic supplier websites.
Secondary data collection:-
In the earlier time, many research professors are working on these AI-based robotic labs. There accept data and findings are very much valuable for this investigation. This research paper also takes some documents in online portals and authorized websites. Conversely, this investigation cannot copy this associated data, and they continuously monitored this document’s validity after applying.
Primary data collection:-
Qualitative and measurable evidence is also applied in this research. The researcher collected all this important evidence in different magazines and organizations that provide AI-based robotic equipment. Some technical figures are also applied in this research, and these diagrams are also collected from reliable sources.
Timeline:-
Figure: – Project Timeline
A project timeline is a parallel bar chart that visually indicates a project plan over time. With the help of this project timeline, the project developer of “AI for robotic empowered smart labs” can follow the duration, and it should be dynamic for effective project completion. These are helpful for planning and expansion projects. The timeline is also helpful for handling the needs between tasks. The upper mention timeline is describing the work plan and the estimated duration of this project. In these timeline displays that the total project duration is 715days where the project starting date is 31st July 2020, and ending date is 28th April 2023. In these project have three dissimilar milestones which are generally applied to elect vital times on the project approach, frequently key purposes. The project designer might apply milestones to mark expected conclusion dates or project assessment sessions.
Conclusion:-
In this research paper are presented the research about AI-based smart robotic lab. In the entire project proposal, the writer describes different concepts about AI and the smart robotic system. In the previous time, most robotic systems are working by the servo motor, which depends on the mechanical architecture. In this research, the researcher can implement some AI-based programming code that should be innovative implementation in robotic architecture. When this kind of robotic system is working at the laboratory, students can take huge benefits for their learnings. Not only that, but these processes are also very much protected, rapid and not risky. In this entire project proposal, the researcher is also framing some research questions that are also answered in methodology sections. This research report is also suffering from specific issues. The initial cost of this robot is very much high, and the system implementation plan should be complex for the student. In this project, the proposal does not describe any simulation techniques that can cause the prime obstruction of these projects. In future work, the researcher should consider emphasis in these parts. Apart from these obstacles, the framed tactic is very beneficial for the student. If the researcher is framing the simulation process according to the prototype, it can be helpful for all learners.
References:-
Bekiroglu, Y., Haschke, R., Karayiannidis, Y., Mariolis, I., McIntyre, J., Malec, J., & Remazeilles, A. (2017). Sarafun, smart assembly robot with advanced functionalities, h2020. Impact, 2017(5), 67-69.
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Gómez-Chabla, R., Aguirre-Munizaga, M., Samaniego-Cobo, T., Choez, J., & Vera-Lucio, N. (2017, October). A reference framework for empowering the creation of projects with Arduino in the Ecuadorian Universities. In International Conference on Technologies and Innovation (pp. 239-251).
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