Robot Programming Using an Arduino Controller and Matlab Discussion

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You will write a draft of the Background section to be turned in before the tech report (note below). Your background section of the technical report must include background research in areas process capability. One team member will write that portion The other two members may choose another topic such as use of robots in industrial applications, future of use of robots in home applications, Robots used in entertainment, machine learning, and other topics related to this project. These are guidelines of topics, students are encouraged to expand upon this selection of topics. If you are unsure if a topic is relevant, contact your instructor. The group should determine which topics will be covered by which team member using the guidelines above. Each team member will select and write about a different topic.

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Engineering 102, Dr. Hamrick, Fall 2019 Project 1 Robot Programming Using an Arduino Controller and Matlab The Objective is to use the Arduino controller, programmed using Matlab, to study the performance characteristics of the motors. Most of the project is individual. I expect students to help one another, but no one should do the project for another student. You may not use another student’s robot for data collection or use another student’s data. Part A: Individual Using the separate handout “Robotic Set Up of the Arduino Controller” and the files provided, configure your Arduino so that it can be controlled by Matlab on your laptop. Build the robot, interface your computer with the Arduino, command it using Matlab, wire at least three motors (torso, shoulder, elbow) through the H-bridges and control each independently. Build the robot using the instructions in the kit. Some words of caution before you start: This will take a couple of hours, so give yourself a clear space to work and bring a lot of patience. Separate the screws and account for all before you start. Some are close in size and are easy to confuse. Be careful to “Snugtight” the screws, but do not over-tighten or they may strip out the plastic. When assembling the transmissions, put in the gears before the nuts, and the nuts must be seated correctly. A wooden toothpick or non-magnetic tool might help, or you can thread one of the correct bolts through the nut to use as a temporary “handle.” You will not need the control box with its toggle switches or batteries, but you are welcome to assemble it, plug in batteries and run the bot manually if you like. If you do, remove all batteries before the next step. Having batteries in the robot can cause many problems. I call the motors out by this designation in line with the human body: Torso is the bottom motor that rotates the arm back and forth, Shoulder is the motor that sits on top of the torso, Elbow is the next one up, Wrist is the next one that is attached to the two links and tilts the gripper, and Gripper is the two fingers at the end. Wire ONE motor through the H-bridge using the instructions. Start with the torso motor. Get that one working so that you can command it with Matlab, then wire the shoulder and elbow motors. It is recommended that you use only pins 3-12 for motors, starting with 12-11 for torso, 10-9 for shoulder, etc. Do not use pins 1,2 or 13 at this time. When you can command all three motors independently, you are ready for data collection. Part B: Individual Process capability - Collect data on the accuracy of your robot: Determine the precision characteristics of one of the motors on your robot. Precision can be thought of as the ability to hit the same mark in the same place every time. This will allow you to determine the tolerance that your robot can hit repeatedly within. You may find that electric motors have different performance characteristics from one to another and when running forward and reverse. Set your initial point: Position a piece of paper in front of your robot with one corner at the front, the orientation of the paper is not very important for this data collection. Attach a marker to the gripper of your robot (rubber bands work well). Position the torso at about a 45 degree angle to the left side of the base so that the marker is roughly in the center of the paper. Write a program that runs the elbow or shoulder motor down and then up so that you make a mark on the paper. Jog that same motor so that the marker is 1/8 inch above the paper. Don’t move that motor any more during this test. Figure 1 Set up of robot with paper Collect data for the accuracy of your torso motor: Write a Matlab program that will rotate the torso motor to the right for 6 seconds, pause for at least ½ second, and rotate back for 6 seconds. Your marker will probably not return to the exact same position. Measure the distance from the fist dot to the second dot and record the value. Without making any other adjustments, run the program again and measure the distance from the second dot to the third dot. Repeat this process, measuring the distance from one dot to the next until you have 10 data points. If your robot drifts significantly you may have to start over, adjusting the torso to a different starting angle in order to get enough cycles before it hits its limit. If 6 seconds is not right for your robot, you may increase or decrease the pause time according to your needs. Fourth dot Third dot D2 D3 Second dot First dot D2 D1 Figure 2 Measuring the distances between dots for data collection. Try to improve the accuracy by adjusting the time intervals: Repeat the process of making an initial dot on the paper. Next change the return pause time intervals so that the marker returns to its starting point. Keep the outbound time the same 6 seconds, but change the return time either longer or shorter depending on the direction it needs to be adjusted. Remember that the pause command in Matlab can be any decimal number, and does not have to be and integer. This will be an iterative “guess and check” process to get the time adjusted so that the marker returns to its starting point. Record your outbound time (6 seconds) and whatever your inbound time is. Repeat the data collection process to get at least 10 data points. Record your data in a table such as the one below making it as long as necessary to collect your data. Note that 0.0 is not valid. If the dots appear to be on top of one another, then you need a measurement instrument with higher resolution. Table 1 Data collection Project 1 Torso Motor Time outbound (sec) Time inbound (sec) Distance (in) Unadjusted 6 6 D1 D2 D3 etc … Time adjusted 6 (your time) D1 D2 D3 etc … Process Capability Analysis: Manufacturers often use statistical analysis to prove that the parts that they make are within tolerances, and use process capability to determine the tolerance that a process can hold. In statistical analysis the Standard Deviation is a measure of the scatter of a given set of data. The higher the Standard Deviation (σ) the wider the scatter. In normally distributed data, 6 x Standard Deviation (6σ) will encompass all but 0.0026 % of all data. Process Capability (Cp) is a ratio of the tolerance range to 6σ. Eqn 1 𝐶𝑝 = (𝑇𝑜𝑙𝑒𝑟𝑒𝑛𝑐𝑒 𝑅𝑎𝑛𝑔𝑒) 6σ A Cp of 1.66 allows a defect rate of only 1 part per million, and is the generally the accepted minimum value for what is known in manufacturing as a “Capable Process.” A Cp<=1.33 yields a defect rate of 63 parts per million and is not acceptable. 1.33 < Cp < 1.66 is only marginally acceptable, and requires corrective action to improve the capability. For the data that you collect, write a Matlab program in a script file that will determine the Average, Median, Maximum, Minimum, Standard Deviation, and tolerance range that you could reasonably maintain. In order to compute the tolerance range, assume that Cp<1.66 is unacceptable, and solve the Cp equation for the tolerance range. Eqn 2 𝑀𝑎𝑥𝑖𝑚𝑢𝑚 𝑇𝑜𝑙𝑒𝑟𝑒𝑛𝑐𝑒 𝑅𝑎𝑛𝑔𝑒 = 6 ∗ 1.66 ∗ σ The program should • • • • • • • Use the data that you recorded as vectors. Determine the Maximum, Minimum, Mean, Median and Standard Deviation of the data. Compute the tolerance range that the robot would be capable of achieving using equation 2. Note the time intervals for each Generate a Matlab table like the one below using fprintf to display the results. Create a fully labeled plot showing BOTH sets of data in ONE figure. Suppress all output to the command window except the requested output The table generated in Matlab should look something like this: Unmodified Time Modified Time ________________________________________________ Time out (s) | 6 | 6 Time in (s) | 6 | # Maximum (in) | ## | ## Minimum (in) | ## | ## Mean (in) | ## | ## Median (in) | ## | ## Std Dev (in) | ## | ## Tol. Range (in) | ## | ## ________________________________________________ Deliverables for Part A: Due 19 Sept along with your Progress Report. You must show me evidence of starting the project. How to do that: Create a short video of your robot running three motors individually, being commanded by Matlab. All three should run through different sets of Arduino pins (six pins in all), not one set of pins rewired to three motors one as a time. You will use both of the chips on your bread board; two sides on one and one side of the other (at minimum). Upload the video to Google drive and share it with me using the directions in the “Steps to Getting a Sharable Link on Google Drive” below. I will extend this deadline only if you have tried but been unable to do so, and have come to me for help before the due date. Asking for help for the first time the day it is due will result in no credit. If you are able to connect the robot and video it, then you don’t have to bring it in. PROJECT DELIVERABLES a) MATLAB Code (Part B) (40%): Deadline:1 Oct 2019 11:59 pm individually submitted code that performs required calculations. Name your file, your firstname_lastname.m. This portion of the project must be done individually. The code must complete the b) Technical Report (Part C) (35%): Deadline: 8 Oct 2019 11:59 pm (Team members will be announced during class. One submission per group. Hardcopy in class and electronic copy uploaded to eCampus. Note about Background: You will write a draft of the Background section to be turned in before the tech report (note below). Your background section of the technical report must include background research in areas process capability. One team member will write that portion The other two members may choose another topic such as use of robots in industrial applications, future of use of robots in home applications, Robots used in entertainment, machine learning, and other topics related to this project. These are guidelines of topics, students are encouraged to expand upon this selection of topics. If you are unsure if a topic is relevant, contact your instructor. The group should determine which topics will be covered by which team member using the guidelines above. Each team member will select and write about a different topic. Important: Students who have done no research have nothing to contribute to their teams, so any student who does not turn in a Background section will be removed from their groups and will not participate in the technical reporting portion of the project, and will receive 0 credit for that portion. Team memberships may be changed if needed. Each section should be about a page of double spaced text (12 pt font), with at least THREE referenced with proper in text citations. Write a technical report that includes uses the IMRAD format taught in ENGR 101. You’ll find review materials in ecampus. The Background section should include a description process capability, including at least three references, not including this document. Use proper in-text citations (Name Page#) and in the end notes in the References section using MLA format. The methodology section should include a description of how the data was collected. The results section should include data from all team members. Combine the data from all team members and describe the similarities and differences between the various robots. Tables for all team members must be included. In your conclusions comment on the potential use of capability studies at the OWI factory. Hand in one hard copy per group and upload a soft copy to e-campus. c) Poster Presentation (15%): Deadline: 8 Oct 2019 must be uploaded prior to the start of class d) Peer Reviews (10%) Deadline: 9 Oct 2019 at 11:59 pm. PROJECT MANAGEMENT DELIVERABLES Gantt Chart, Intro and Background, and Team Charter are required components and will be included in the assignment portion of the course grade. Due dates for these items will be set by your instructor: A) Team Charter and Gantt Chart due 12 Sep 2019, 11:59 pm, Group assignment B) Background section of tech report, 22 Sep 2019, 11:59 pm, Individual assignment. See above for guidelines. C) Interim progress report (executive summary) and updated Gantt Chart , and Part A of robot build. Due 19 Sep 2019, 11:59 pm, Group assignment Note: the tentative date for Exam 1 is 24 Sep 2019 STEPS TO GET SHARABLE LINK FOR GOOGLE DRIVE FOLDER 1. Click the arrow next to the laster folder name, then click Share 2. Click “Get sharable link” in the upper right corner. 3. Select the drop down arrow, then click “More” 4. Select “On – Anyone with the link”, then click Save. 5. Finally, copy this link into the eCampus assignment submission box and submit! ...
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Process capability
Robotics is no longer a new time in most of the industries across the economic spectrum.
It features as a way of transferring human capability to machines through the computer
integrated manufacturing. A cross-section of the companies now depend on the computer-aided
production is creating an environment in which the devices can deliver quality products at a little
cost. Developing a perfect robot will be valuable in specific areas. In this case, the areas process
capability of the robot is exceptional. It is something that everyone would want to understand
and use. It will help develop the program and the process with the ability to earn excellent
knowledge of every process.
The management needs to put in place the simulation and systems relating to robotics
operations. Companies will be able to make the right decisions on the selection using the
necessary selection models....

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