[Solved] CS7638 Gem Finder Project

Project DescriptionThe goal of this project is to give you practice implementing a SLAM module and a robot controlsystem that uses it to navigate through a world.Part A (worth 40%) asks you to build a SLAM system that can keep track of where your robot islocated after a series of movements (using measurements to landmarks). Complete the SLAMclass in the gem_finder.py file. The movements and measurements will have noise.Your robot will be dropped into an unknown territory by a team seeking to extract special gemsin the area. The robot has special sensors that are able to detect the gems in the region. Themeasurements from these sensors can be used to help the robot navigate. The sensors willprovide the bearing and distance to the gem (relative to the location on the map). Both ofthese measurements contain noise. The amount of noise will be proportional to the distanceaway from the robot. For example a close gem will have a small amount of noise, while a faraway gem will have a larger amount of noise. Since this noise value is not provided, you willneed to come up with a way to estimate the noise, while maintaining this proportionalconstraint.Your robot should make a map of the environment, using its starting location as the origin (0,0)by taking advantage of the measurements to the gems to maintain a good estimate of its ownposition relative to the initial (0,0) drop-off location.In part A, your robot will receive a set of measurements as it follows a pre-scripted set ofmovements, and your SLAM module will need to calculate and report your robots position aftereach measurement and movement (relative to the arbitrary (0,0) staring point). [You do notguide the robot in part A and do not extract any gems, this part is only to test your SLAMmodule.]Part B (worth 60%) asks you to navigate your robot around the environment to extract gemsprovided to you in a list. Complete the GemExtractorPlanner class in the gem_finder.py file.Your commander will provide you with a list of needed gems. You will need to collect one ofeach kind of gem in the list. You can collect them in any order, you dont have to follow theorder provided in the list. You do not need to extract all gems in the environment, only the onesin the provided list.There is a time penalty for extracting dirt (failing to extract a gem). This case happens whenyou attempt to extract in a location that does not contain a gem of the type you specified(within a minimum extraction distance). Your robot must be within this pre-defined distance(0.15) of the gem in order to extract it successfully. As soon as the extraction is successful, thegem will be removed from the environment. When a gem is extracted from the terrain, it nolonger exists in the terrain, and thus wont return a measurement. You must specify the type ofgem you are intending to extract when you attempt to extract. Only this kind of gem will beextracted if it is within the defined radius, if not there will be a time penalty.Your robot has a maximum turning angle [pi/2] and distance [passed using a parameter] that itcan move each turn. Movement commands that exceed these values will be ignored and causethe robot to not move.Note that your robot will never have access to the map of where the randomly scattered gemsare located, only a list of the gems needed.Submitting your AssignmentYour submission will consist of the gem_finder.py file (only) which will be uploaded toGradescope. Do not archive (zip,tar,etc) it. Your code must be valid python version 3.6 code,and you may use external modules such as numpy, scipy, etc that are present in the UdacityRunaway Robot auto-grader. [Try to ensure that your code is backwards compatible with numpyversion 1.13.3 and scipy version 0.19.1]Your python file must execute NO code when imported. We encourage you to keep any testingcode in a separate file that you do not submit. Your code should also NOT display a GUI orVisualization when we import or call your function under test. If we have to manually edit yourcode to comment out your own testing harness or visualization you will receive a -20 pointpenalty.Testing Your CodeWe have provided testing suites similar to the one well be using for grading the project, whichyou can use to ensure your code is working correctly. These testing suites are NOT complete,and you will need to develop other, more complicated, test cases to fully validate your code.We encourage you to share your test cases (only) with other students on Piazza.You should ensure that your code consistently succeeds on each of the given test cases as wellas on a wide range of other test cases of your own design, as we will only run your code onceper graded test case. For each test case, your code must complete execution within theproscribed time limit (5 seconds) or it will receive no credit. Note that the grading machine isrelatively low powered, so you may want to set your local time limit to 2.5 seconds to ensurethat you dont go past the CPU limit.A visualization file has been provided to aid in debugging. The visualization will plot 5 pieces ofdata: real location of robot, estimated location of robot, real location of gems, estimatedlocation of gems, type of gem (A, B, etc) present in environment. The real location of therobot will be a large red dot. The estimated location of the robot will be a small red dot. Thereal location of a gem will be a large grey dot. The estimated location of a gem will be a smallblack dot. The type of gem will be next to the real location. When the robot extracts a gemfrom the environment, the letter will no longer exist next to the real location (to indicate it hasbeen removed).The estimated points to plot need to be returned from next_move as a 2nd (optional) value inthe form of a dictionary. The keys will be the landmark id and the values will be x,y coordinates.The key representing the robots estimated location will be self. {self: (.2, 1.5),123: (.4,1.9)}Usage:python visualize.py [-h] [part {A,B}] [case {1,2,3,4,5,6,7,8,9}]Example to run the visualization:python visualize.py part B case 5We are using the Gradescope autograder system which allows you to upload and grade yourassignment with a remote / online autograder. We may also choose to use the last gradeyou receive via the remote autograder as your final grade at our discretion. (See theOnline Grading section of the Syllabus.)Academic IntegrityYou must write the code for this project alone. While you may make limited usage of outsideresources, keep in mind that you must cite any such resources you use in your work (forexample, you should use comments to denote a snippet of code obtained from StackOverflow,lecture videos, etc).You must not use anybody elses code for this project in your work. We will use code-similaritydetection software to identify suspicious code, and we will refer any potential incidents to theOffice of Student Integrity for investigation. Moreover, you must not post your work on apublicly accessible repository; this could also result in an Honor Code violation [if anotherstudent turns in your code]. (Consider using the GT provided Github repository or a repo suchas Bitbucket that doesnt default to public sharing.)Frequently Asked Questions (F.A.Q.)Q: How can I uniquely identify gems in the environment?A: Each gem will have a unique id. Although there may be more than one of the same type ofgem in the area, each will have a different unique id.Q: What are the (x,y) return values from process_measurement() and process_movement() inpart A relative to? And how are they different?A: Both of them return your best guess for the position of the robot relative to the startinglocation (0,0). The difference between them is that one of them gives an estimation of therobots position after a measurement, and the other after the robot has moved.Q: Which way is the robot facing when it lands?A: Although slightly unrealistic, your robot will always have a bearing ofzero degrees when it lands. (You are welcome.