{ "key_pair_value_system": true, "answer_rating_count": "", "question_feedback_html": { "html_star": "", "html_star_feedback": "" }, "answer_average_rating_value": "", "answer_date_js": "2024-09-13T00:04:19-04:00", "answer_date": "2024-09-13 00:04:19", "is_docs_available": "", "is_excel_available": "", "is_pdf_available": "", "count_file_available": 0, "main_page": "student_question_view", "question_id": "10520982", "url": "\/study-help\/questions\/using-the-unicycle-model-you-implemented-above-you-will-now-10520982", "question_creation_date_js": "2024-09-13T00:04:19-04:00", "question_creation_date": "Sep 13, 2024 12:04 AM", "meta_title": "[Solved] Using the Unicycle model you implemented | SolutionInn", "meta_description": "Answer of - Using the Unicycle model you implemented above, you will now command the system to reach a goal position. Start with o | SolutionInn", "meta_keywords": "unicycle,model,implemented,will,command,system,reach,goal,position,start,open,-", "question_title_h1": "Using the Unicycle model you implemented above, you will now command the system to reach a goal position. Start with open - loop control, i", "question_title": "Using the Unicycle model you implemented above, you will now command the", "question_title_for_js_snippet": "Using the Unicycle model you implemented above, you will now command the system to reach a goal position Start with open loop control, i e , measure the intial state ( returned by env reset ) and then calculate a sequence of actions to apply After that sequence is computed, run the simulator forward for several steps, and at each step, simply grab the corresponding control value from that pre computed sequence You can use this example open loop control policy implementation as a first try Your job is to implement a smarter open loop control policy that gets the system to reach ( close ) to the goal Remember you are only provided with the initial state, goal position, and the maximum number of steps allowed you can't access the system's state once it has started moving That would be closed loop control, which we'll implement next Deliverables Implement the open loop control policy, which should produce a sequence of control commands that will lead to the goal This can be a very simple hard coded policy ( e g , always send the same v , w ) Generate 1 plot that shows your open loop controller drives the noise free system to the goal ( it only has to work for 1 test case ) Include the path taken and the start goal coordinates in your plot Generate 1 plot that shows your open loop controller running on the noisy system ( it ' s ok if it doesn't work on this system ) Include the path taken and the start goal coordinates in your plot def open loop control policy ( init state np ndarray, goal np ndarray, num steps int 1 0 ) list np ndarray Your Implementation Here raise NotImplementedError return control sequence o np random seed ( 0 ) max num steps 2 0 0 env unwrapped motion model Unicycle (", "question_description": "