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Automation & Robotics Assignment Sample

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Introduction

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Robotics is a design, intersection, use and construction of machines in order to perform some tasks traditionally by human beings. Another definition of the robotics is, it is a convergence of engineering and science, where the engineer used different types of technology, which produces the machines, are known as a robot. Automation is a type of technology, which helps a process or procedure to complete its job with human assistance. Automation acts as a technique, which is used to create a process, apparatus and it, also operates the systems automatically.
There are similarity and dependency between automation and robotics. Automation is a process and robotics is a machine, the engineer used the different types of automation technology in order to create a perfect robotics function. With this, there was a difference also; automation is a process, which used the computer science and physical machine in order to perform the tasks, which are usually done by humans. In the other hand, the robotics is the design and creating process of robots, which is used to perform some certain tasks. Tin this project the researcher is discussed about different functions and statistical information about the automation and robotics in a proper manner.

Task A

In order to create a smooth single motion minimum of four constraints on θ(t) are apparent.
2 constraints on the value of the functions come from the initial selection and final value:
θ(0) = θ0
θ(tf) = θf ……………………………………………(7.1)

As a supplementary two constraints are that the functions, which are continuous in velocity, and it, in this case, means that, the final and initial velocity is equal to zero.
θ1(tf) = θf ……………………………………..(7.2)
θ1(0) = θ0
The four constraints are satisfied by the polynomial of a minimum third degree. These four contrast peerlessly specified a specific cubic. The form of the cubic is:
θ(t)= a0+ a1t + a2t2 + a3t3 …………………………………..(7.3)
Therefore, the acceleration and the joint velocity with the path are clear:
θ1(t) = a0+ a1t + 2a2t+ 3a3t2
θ2(t) = 2a2+ 6a3t………………………………(7.4)
Attaching the equation of the 7.3 and 7.4 with the 4 constraints surrenders four equations in four unauthorised:
θ0 = a0
θf= a0+a1tf+ a2t2f
0= a1
0= a1+2a2tf+3a3t3f ………………………………………(7.5)
Solved the equation for the ai , we acquire that:
a0 = θo,
a1 = 0,
a2 =3/t2f* (θf- θ0)
a3 =-2/t3f * (θf- θ0) …………………………..(7.6)
Using the equation number 7.6, the users can calculate the cubic polynomial, which connects the initial position of the joint- angle with final positions. This solution is used for the cases, when the joints start and finishes at the zero.
Cubic polynomial with a path for a via points:
Yet, the researcher contemplates the motions defines by the duration and last goal points. In the general versions, it allows the paths in order to specify that attached the intermediate via points. In case the manipulator is to come to rest at every single points, then the user can used the cubic solution 7.3.
In the case of single goal point, every via points are used to specified in terms of position and orientation of the tool frame which are related with the station frame. Every via points are converted in a set of joint angles by the inverse kinematics application. Then it is considered the computing cubic problem which are connects the value of the via points for every joint with each other in a smooth manner.

At the via points, if the velocity of the joint angle are known, then the users can create the cubic polynomial as the before done part, but in this case the velocity constraints are not 0. Then the constrains of the equation number 7.3 becomes
θ1(tf) = θ1f ……………………………………..(7.9)
θ1(0) = θ10
The four equations are used to defined the general cubic are
θ0 = a0
θf= a0+a1tf+ a2t2f+a3t3f
θ10= a1
θ1f= a1+2a2tf+3a3t2f ………………………..(7.10)
Solving these equations for the value of the ai, the researcher acquire,
a0 = θo,
a1 = θ1o,
a2 =3/t2f * (θf- θ0)-2/tfθ10 – 1/ tfθ1f
3 =-2/t3f * (θf- θ0) + 1/ t2f (θ1f+θ10)……………………………..(7.11)
Using the 7.11 the users can calculate the cubic that connects the initial and final position with the final and initial velocities.
If the users have the velocity than of each via points, then the user can apply the equation 7.11 in every segment in order to find the needed cubic. There are several path, which guides to specified the desired velocity at the via points.
The users can specified the velocity of every visa points in view of angular velocity and Cartesian linear velocity of the tool frame.
The system also can chose the velocities automatically at the via points by applying a suitable heuristic in joint space or Cartesian space.
The system also can chose the velocities in such way because throughout points the accelerations to be continuous (Pan et al. 2018).
In the first option the Cartesian velocity via points are mapped in order to desire the rates of joints by applying the inverse manipulator’s jacobian evaluated via points. In case the manipulator is present in the singular point and in the particular via point get the user is not allowed to control the arbitrary velocity at the via points.
At the second option, the system selects the reasonable intermediate velocity by using some heuristics. Based on the selected path, via points which are shown in the figure number 5, where the joints are θ, the following graph is developed.

In this case the researcher made a choice of joint angle velocities at the via points, in order to point with small line segments represented by the tangents to the curve at every via points. This choice is the application result of a computationally conceptuality heuristic. The slope of this line are changed in the points where the velocities are 0. If the slope of the line is not changed than, the users have to choose two slopes as a replacement of via points. In this manner the desired position via points alone and the system can choose the velocity in every point.
In the third option the system, choose the velocities in a manner that the accelerations is in continuous manner at via points. In order to do this a latest approaches are required. In this types of spline, the collection of data the researcher replaced the two velocities constraints in the two cubic connections with the two constrains which accelerations and velocity are continuous.
Cubic trajectory expression
Cubic trajectory is a type of trajectory which defines a planning procedure that guides the robots to move from point A to point B when by avoiding collisions. This can be compute in both continuous and discrete method. It is a very important area in robotics because it helps to control the autonomous vehicle and a robot is a part of autonomous vehicle. It should be adequately smooth and create limits on joint velocity, variables, torques or accelerations. In the below part the researcher has added the equation of the cubic trajectory expression, which guides the users to find the value of cubic trajectory.
p(t) = a0+a1t+a2t2+a3t3
p?(t) = a1+2a2t+3a3t2
p0=a0+a1t0+a2t02+a3t03
V0=a1+2a2t0+3a3t02
p0=a0+a1t0+a2t02+a3t03
pf=af+a1tf+a2tf2+a3tf3
Vf=a1+2a2tf+3a3tf2
?(1&t0&t02&t03@0&1&2t0&3t02@1&tf&tf2&tf3@0&1&2tf&3tf2) * ?(a0@a1@a2@a4) = ?(P0@V0@Pf@Vf)
Ma=b
A=M-1b
To improve the concept of this task three different cubic trajectory expression related curve has been developed by using the value of T0 = 8.0 and the value of P0 = 66. Application of the value of T0 in the Matlab coding of cubic trajectory expression the below curve has been observed:

This curve helps to observe the robot planning procedure for avoiding the collision. The below figure analyse the coding part of this curve development in Matlab platform:

This plot evaluates the T0 and P0 value in the Matlab platform. This evaluation helps to analyse the spline collection and velocity optimization for the initial stage.

The above curve helps to optimize the position trajectory and velocity of the autonomous vehicle. For developing this plot the ‘cubicpolytraj’ function has been used in the mat lab file. This function helps to generate the curve trajectory plot in Matlab.

Task b


PLC

PC stands for the programmable logic controller. It is an industrial digital computer, which is adapted and ruggedized for the manufacturing process control, such as robotic devices, assembly line, and many other activities, which require ease of programming, process fault diagnosis and high-level reliability (Pham et al. 2018). The main job of the programmable logic controller in the industrial plant and factories is, to control the pumps, motors, crucial bankers, light, fan and other machines. Power supply, processor, communication, communication protocol and media, redundancy, ladder diagram are the main components of the PLC.
PLC is somehow similar to the typical microcomputers. PLC is in the function and in the operations when all the components of the PLC are placed in a proper manner (Wajcman, 2017). In order to control the PLC the users have to maintain some steps in a lopping manner, which are mentioned in the below

section:

Input scan: it is used to recognise the condition of different input devices that are linked or connected with the PLC at any time.
Output scan: It associates to deactivate or activate with the devices, which are connected with the PLC.
Program scan: It is used to execute or effect the application, which is created by the users.
Housekeeping: It requires the transmission between the terminals and the other diagnostics (Matari?, 2017). This also attached the processor, power supply and the mounting or rack, which are referred by the other person.

PLC programming is a technique, which is used to operate the entire PLC function. It receives the information, which is relayed by the sensors, and input devices that is connected with each other to do this job. It then forwarded to process the data or information. The output triggering assumed on the programmed parameter following the upper mentioned steps.
The PLC also used to monitor, control, and observe some important data such as the level of the productivity of the machine and operating temperature (Wang & Siau, 2019). This also attached the generation of the alarm in terms of any possible machine malfunctions.
From the preceding, the PLC system is described in a proper manner. It attached some important components and the process of its works. The programming of the PLC system is very important in the sensor control and monitor control. This makes sure that it is readily used in the organisation where control systems are paramount and instrumental.


Teach pendant

Teach pendant is a type of programming, which is used to distribute an inborn way in order to interact with the robots (Hemming, 2018). It attached the uses of handheld control terminal, which is known as teach pendant. The teach pendant is one of the important robotics programming, which is used by the engineer in order to create an effective robot. It is mainly used to control the motion of the robot. By using this, the organisations can teach some specific locations or points and the sequence of the path to the robot. Most traditional robots are created by using the teach pendant in order to make the function of the robot familiar to technicians. The teach pendant allows the precise positioning, that the robot can program by using the world coordinates or numeric coordinates or robot coordinates systems (Tilley, 2017).
The devices of the teach pendant are required to control the industrial robot remotely. This device allows the controllers in order to work with the robots without the requirement for the tethering in order to fix the terminal. It offers different types of settings in order to reign the robot and employs the design of new features and new capabilities. It used a control box in order to create a program for the motions of the robot, which is known as the teach box. In this case, the pendant is used to define the robot in a systematic manner. Mainly the teach pendant is used to handled the wired device and wireless device.
Teach pendant is most powerful robotics program. According to the British automation and robot association, near about 90% of robots are created by using this program. The features of the teach pendant are changed in a day-by-day manner and the latest teach pendant are looks like a touchpad tablet.


Advantages

The most traditional robots are created by using the teach pendant, which makes the robots more familiar with to technician. It creates some great and simple movement in the robot, such as paint a straight line over a flat surface.


Disadvantages

It is difficult than the other program, so the users need proper training in order to work with thus program. Unruly to the entire system because, the robots downtime. The robot must have to put in the teach mode and the entire operations by using the robot halted until it has been programmed (Abd Rashid et al. 2018).

Task c

The controller is a single who has responsibility for entire activities, which are related to the accounts, including the managerial account, high-level accounts, and finance activities in an organisation. In the robotics, the main job of the controller is to connect the robots with the computer that keeps the arm pieces for working together. In this case, the computer is work as a controller. The controller function is work as the brain of the robot. The entire function of being a robot is controlled by the controller, such as the movement of the arm, feet, and many other jobs. The controller also creates the network with the other system, so the robot can work together with other practices, machines and robots.
There are different types of controller are available in the robotics industry, such as Proportional plus Integral control, Proportional control, ON-OFF control, integral control and so on(Fioriniet al. 2017). Different types of proportional control are used the proportional term and integral term as a PI controller. The Kc value is the multiplier on the integral term and proportional error and the highest vale creates the controller more hostile at the stage of the correspondence of the error away from the via point. ON-OFF controller is used to on the robotics system and the off the robotics system. It acts as a main controller in the robot.
The controller is a device which takes one or more than one input from the users and then adjusts it as an output so that the function of the connected devices stay in a controlled manner(Bento, 2018). Many engineers used the simple motor controller and microcontrollers, which can be tasked with the different types of control, outputs and perform closed-loop control.
In the robot, control system is used to allow the robot for the various types of function and movement of the different parts of the robots, also execute particular forces and motion in the existence of the unforeseen errors. Teamwork is also very important for robots. The interaction level between the machines and humans fixed how adaptable and versatile the robot is. In the RPA state, the robot controller takes various roles. It acts as a primary repository in order to define facilitates and jobs version control. It also used to safely stored character for the application of the business and distribute them to robots as per requirement(Caiet al. 2018).

The upper mentioned image means contains the Simulink of the trajectory. These all Simulink is created in the MATLAB software. Simulink is adding on product to the MATLAB. Which provides a graphical, interactive environment for the simulating, analysing and modelling of the dynamic system? It starts the rapid production of the virtual prototypes in order to visualise the concept of the design at any level, with the details and the minimal effort.
MATLAB is a programming platform, which is mostly created for engineering and scitist. The MATLAB function is totally run depend on the MATLAB language and matrix-based language. It is used to present the most natural expression of computational mathematics. People used the different functions of the MATLAB because, it used a huge range of applications including machine learning and deep learning, communication and signal processing, control system, computational finance, computational biology and so on. The full name of the MATLAB is MATrixLABorator and it is written in order to provide easy access to the matrix software which are developed by the EISPACK and LINPACK project.
There is no comparison between MATLAB because Simulink is acting as a tool, which is provided by the MATLAB. By using the MATLAB the user can simulate the model of the system more readable because it represents any topic in a graphical manner.

Conclusion

This project is totally created based on the information of the robotics and the automation. Robotics is a part of engineering, which deal with the application and design of the robots and the use of computer science in order to manipulate and process the machine functions and data in a proper manner. Automation is a use of information technologies and control system, which is used to decrease the requirement of the job in the construction of the different services and goods. The different types of advantages, disadvantages of the automation and robotics are attached in this project. The relation and the difference between robotics and automation are also mentioned in this project. In order to does this job the researcher have to use different types of mathematical operation related to the topic. In order to complete the mathematical operation, and visualisation of the operation the researcher also have to use some programme. In order to run the programming, the researcher used the MATLAB software in this project. From the task a, task b and task c the learner can gather a huge amount of knowledge about the robotics and automation in a proper manner with a clear visualisation and codes and mathematical operations.

References

Abd Rashid, M. N., Abdullah, M. R., Ismail, D., &Mahyuddin, M. N. (2018). TOWARDS AUTOMATION AND ROBOTICS IN INDUSTRIALISED BUILDING SYSTEM (IBS): A Retrieved on 5th January 2021 from: http://www.academia.edu/download/57530197/Towards_Automation_and_Robotics_in_Industrialised_Building_System_Mohd_Najib_Abd_Rashid.pdf
Bento, A. C. (2018). Internet of Things: An Experiment with Residential Automation for Robotics Classes. International research journal of management, IT and social sciences, 5(2), 113-119 Retrieved on 5th January 2021 from: https://sloap.org/journals/index.php/irjmis/article/download/51/1064
Cai, S., Ma, Z., Skibniewski, M., Guo, J., & Yun, L. (2018). Application of automation and robotics technology in high-rise building construction: an overview. In ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction (Vol. 35, pp. 1-8). IAARC Publications Retrieved on 6th January 2021 from: https://www.researchgate.net/profile/Zhiliang_Ma/publication/328377767_Application_of_Automation_and_Robotics_Technology_in_High-Rise_Building_Construction_An_Overview/links/5c94f6a1299bf1116940876d/Application-of-Automation-and-Robotics-Technology-in-High-Rise-Building-Construction-An-Overview.pdf
Fiorini, S. R., Bermejo-Alonso, J., Gonçalves, P., de Freitas, E. P., Alarcos, A. O., Olszewska, J. I., ... & Li, H. (2017). A suite of ontologies for robotics and automation [industrial activities]. IEEE Robotics & Automation Magazine, 24(1), 8-11 Retrieved on 4th January 2021 from: https://ieeexplore.ieee.org/iel7/100/7886370/07886384.pdf
Hemming, J. (2018). Automation and robotics in the protected environment, current developments and challenges for the future. In 28th Club of Bologna Members’ Meeting (pp. 1-7) Retrieved on 4th January 2021 from: https://www.clubofbologna.org/ew/ew_proceedings/2018_S3.3_KNR_HEMMING_mf.pdf
Matari?, M. J. (2017). Socially assistive robotics: Human augmentation versus automation. Science Robotics, 2(4), eaam5410 Retrieved on 7th January 2021 from: https://robotics.usc.edu/publications/media/uploads/pubs/pubdb_968_6824a9b17e2c4726a6d68298af0f0823.pdf
Pan, M., Linner, T., Pan, W., Cheng, H., & Bock, T. (2018). A framework of indicators for assessing construction automation and robotics in the sustainability context. Journal of Cleaner Production, 182, 82-95 Retrieved on 8th January 2021 from: https://mediatum.ub.tum.de/doc/1484303/file.pdf
Pham, Q. C., Madhavan, R., Righetti, L., Smart, W., &Chatila, R. (2018). The impact of robotics and automation on working conditions and employment. IEEE Robotics & Automation Magazine, 25(2), 126-128 Retrieved on 8th January 2021 from: https://personal.ntu.edu.sg/cuong/docs/Pham-et-al-RAM-2018.pdf
Salcic, Z., Atmojo, U. D., Park, H., Chen, A. T. Y., Kevin, I., & Wang, K. (2017). Designing dynamic and collaborative automation and robotics software systems. IEEE Transactions on Industrial Informatics, 15(1), 540-549 Retrieved on 7th January 2021 from: https://researchspace.auckland.ac.nz/bitstream/handle/2292/42470/08234634.pdf?sequence=2&isAllowed=y
Tilley, J. (2017). Automation, Robotics, and the Factory of the Future. McKinsey. https://www. mckinsey. com/business-functions/operations/our-insights/automation-robotics-and-the-factory-of-the-future Retrieved on 6th January 2021 from: https://www.mckinsey.de/~/media/McKinsey/Business%20Functions/Operations/Our%20Insights/Automation%20robotics%20and%20the%20factory%20of%20the%20future/Automation-robotics-and-the-factory-of-the-future.pdf
Wajcman, J. (2017). Automation: is it really different this time?. The British journal of sociology, 68(1), 119-127 Retrieved on 3rd January 2021 from: http://eprints.lse.ac.uk/69811/1/Wajcman_Automation%20is%20it%20really%20different%20this%20time.pdf
Wang, W., &Siau, K. (2019). Artificial intelligence, machine learning, automation, robotics, future of work and future of humanity: a review and research agenda. Journal of Database Management (JDM), 30(1), 61-79 Retrieved on 3rd January 2021 from: https://www.researchgate.net/profile/Keng_Siau/publication/333423274_Artificial_Intelligence_Machine_Learning_Automation_Robotics_Future_of_Work_and_Future_of_Humanity_A_Review_and_Research_Agenda/links/5cf48f4b92851c4dd0240f42/Artificial-Intelligence-Machine-Learning-Automation-Robotics-Future-of-Work-and-Future-of-Humanity-A-Review-and-Research-Agenda.pdf

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