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https://gitlab.ewi.tudelft.nl/ee2l1/2025-2026/A.K.03.git
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1065 lines
547 KiB
Plaintext
1065 lines
547 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"\n",
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"[Table of Contents](0_Table_of_Contents.ipynb)\n",
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"\n",
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"# Chapter 4: Module 2 - Reading KITT Sensor Data\n",
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"\n",
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"**Contents:**\n",
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"* [Distance Sensor](#distance-sensors)\n",
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"* [The Microphones](#the-microphones)\n",
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"* [FAQ](#faq)\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-11-28T08:43:34.403324Z",
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"start_time": "2025-11-28T08:43:33.090082Z"
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}
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},
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"source": [
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"# Import necessary libraries\n",
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"import time\n",
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"import numpy as np\n",
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt\n",
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"import csv\n",
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"\n",
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"# Uncomment one of the following lines depending on your setup\n",
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"\n",
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"# If you are using the real car, uncomment the next lines and comment the simulator lines\n",
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"from serial import Serial\n",
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"import sounddevice\n",
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"\n",
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"# If you are using the simulator, uncomment the next lines and comment the real car lines\n",
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"# from KITT_Simulator.serial_simulator import Serial\n",
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"# from KITT_Simulator.sounddevice_simulator import sounddevice\n",
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"\n",
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"# Note: After changing the import statement, you need to restart the kernel for changes to take effect."
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],
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"outputs": [],
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"execution_count": 1
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"KITT relies on its sensors to drive autonomously. It is equipped with:\n",
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"1. Two front-mounted distance sensors.\n",
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"2. Five microphones positioned around the field to record audio signals from KITT's beacon and relay them to the soundcard, after which they can be read by your PC.\n",
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"\n",
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"This task focuses on reading data from the distance sensors to avoid obstacles and processing the microphone data from the field.\n",
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"\n",
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"**Preparation**\n",
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"- Ensure KITT is operational and properly set up.\n",
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"- Reserve a time slot for testing on a field equipped with microphones and an audio card.\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Distance Sensors\n",
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"\n",
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"KITT’s front distance sensors use ultrasonic technology. Two SRF02 modules, mounted on the left and right sides, measure the distance to obstacles. These \"parking sensors\" work by emitting a 40 kHz pulse and measuring the time it takes for the echo to return. This time is converted into a distance measurement.\n",
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"\n",
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"- Each sensor requires a minimum of 66 ms between readings, as specified in the SRF02 datasheet (available on Brightspace or at `Files/Datasheets/srf02.pdf`).\n",
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"- The system is configured with a 70 ms cycle time; the left and right sensors take turns recording measurements.\n",
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"- These measurements are stored in a buffer on KITT's microcontroller, with each new reading overwriting the previous one. When you request the KITT status, you will obtain a copy of the current buffer values.\n",
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"\n",
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"<img src=\"pictures/srf02-ultrasonic-sensor.jpg\" alt=\"Ultrasonic Sensor\" width=\"400\" height=\"240\">\n",
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"\n",
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"### Step 0: Characteristics of the Distance Sensors\n",
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"\n",
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"Using the readings on the car display, report on the following questions:\n",
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"\n",
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"1. What is the accuracy of the distance sensors? Does this change with distance?\n",
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"2. What are the minimum and maximum distances the sensors can measure?\n",
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"3. What is the field of view of the distance sensors (beam angle)?\n",
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"\n",
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"To measure this field of view, move an obstacle from left to right over a line, at about 1 m distance from the sensors, and observe when the sensors start to 'see' the object.\n",
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"\n",
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"The field of view is important when making recordings: you should realize that the distance sensors may detect chairs, bags, etc., and then make false readings. This happens even if these objects are not straight in front of the sensors. (The field of view does depend on distance.)\n",
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"\n",
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"**Note:** Do not copy the questions into your report, but naturally include the information in your report as part of your discussion.\n",
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"\n",
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"### Step 1: Status Command\n",
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"\n",
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"To ensure you can experiment at home, we have added the status command to the simulator. The simulator will accurately simulate the sensor distances, but not its behavior. Make sure to test on the real car frequently.\n",
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"\n",
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"As you have learned in the previous module, you can ask KITT to capture a status command by writing `\"S\\n\"` to the serial port. Then you have to read the message using `read_until`; this will generate a binary message that you need to decode. KITT always ends its message with the end-of-transmission character (0x04). The response contains three sections:\n",
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"1. Audio beacon status and settings\n",
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"2. PWM values for the motors\n",
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"3. Sensor readings"
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-11-21T08:40:49.777160Z",
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"start_time": "2025-11-21T08:40:48.574633Z"
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}
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},
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"source": [
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"### Student Version ###\n",
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"\n",
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"serial = Serial('COM4', 115200)\n",
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"serial.write(b'Sd\\n')\n",
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"status = serial.read_until(b\"\\x04\")\n",
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"status = status.decode('utf-8')\n",
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"print(f\"Car status is:\\n\\n{status}\")\n",
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"\n",
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"serial.close()"
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],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Car status is:\n",
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"\n",
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"USL99\n",
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"USR51\n",
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"\u0004\n"
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]
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}
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],
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"execution_count": 45
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-11-21T08:52:18.034321Z",
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"start_time": "2025-11-21T08:52:18.022808Z"
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}
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},
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"cell_type": "code",
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"source": "serial.close()",
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"outputs": [],
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"execution_count": 51
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"If you only need distance measurement information, you can request it separately:\n",
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"\n",
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"```python\n",
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"serial.write(b'Sd\\n')\n",
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"```\n",
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"\n",
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"This returns only the left and right distance sensor values, filtering out the rest of the status report.\n",
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"\n",
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"### Step 2: Extracting and Isolating Distance Data\n",
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"\n",
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"Assuming you have received the full status information from KITT, you can extract and isolate the distance sensor readings (left and right) from the status report.\n",
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"\n",
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"After sending the status command (`b'S\\n'`), the response will contain a variety of information, including the distance measurements. Now write a Python function to extract the distance data from the status report.\n",
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"\n",
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"1. **Extract the distance measurements**:\n",
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"\n",
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"The distance values are typically embedded in the `Sensors` section of the status response. You can process the `status` output to isolate just the left (`L`) and right (`R`) distance sensor values. Write a function to extract these values.\n",
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"\n",
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"*Hints:*\n",
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"\n",
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"- Use `decode('utf-8')` to convert bytes to a string.\n",
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"- Use `splitlines()` to separate the status message into individual lines.\n",
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"- Look for the line that contains `\"Dist.\"` to find the distance measurements.\n",
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"- Use `split()` to break the line into individual words.\n",
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"- Be cautious of the positions of the distance values in the list; adjust indices as necessary.\n",
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"\n",
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"**Note:** If you use the `Sd` status command, you retrieve less info and can write a faster function! The parsing of the status string is also easier."
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-11-21T08:49:45.232118Z",
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"start_time": "2025-11-21T08:49:45.222261Z"
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}
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},
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"source": [
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"### Student Version ###\n",
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"\n",
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"def extract_dis ():\n",
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" serial = Serial('COM4', 115200)\n",
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" serial.write(b'S\\n')\n",
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" _status = serial.read_until(b'\\x04')\n",
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" _status = _status.decode('utf-8')\n",
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"\n",
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" lines = _status.splitlines()\n",
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"\n",
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" # Initialize variables to hold distance values\n",
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" dist_L = None\n",
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" dist_R = None\n",
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"\n",
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" # Iterate over each line to find distance data\n",
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" for line in lines:\n",
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" if \"Dist.\" in line:\n",
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" words = line.split()\n",
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" # Extract distance values based on their positions\n",
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"\n",
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" # Assign dist_L and dist_R accordingly\n",
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" dist_L = words[3]\n",
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" dist_R = words[5]\n",
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" break # Exit the loop after finding the distances\n",
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"\n",
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" # Print the extracted distance values\n",
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" print(f\"Left Distance: {dist_L}\")\n",
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" print(f\"Right Distance: {dist_R}\")\n",
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"\n",
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" serial.close()\n",
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"\n",
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" return dist_L, dist_R"
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],
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"outputs": [],
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"execution_count": 46
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-11-21T08:38:36.110680Z",
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"start_time": "2025-11-21T08:38:34.392005Z"
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}
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},
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"cell_type": "code",
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"source": "extract_dis()",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Left Distance: 99\n",
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"Right Distance: 51\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"('99', '51')"
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]
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},
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"execution_count": 44,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"execution_count": 44
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"2. **Determine how fast you can read out (and process) your distance data** by writing a script that requests the status 100 times. You can calculate the average delay for this operation (and its standard deviation); you could also present the results in a histogram. To measure delays, you will need to keep track of time:\n",
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"\n",
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"```python\n",
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"start_time = time.time() # Initialize\n",
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"current_time = time.time() - start_time # Find current time since initialization\n",
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"```\n",
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"\n",
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"If you can read out the sensors faster than 70 ms (or is it 140 ms?), reason if you will obtain duplicate values from the buffer.\n",
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"\n",
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"**Student Task:**\n",
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"\n",
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"- Write a script that sends the status command 100 times, recording the time taken for each read.\n",
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"- Store the time intervals in a list.\n",
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"- After collecting the data, calculate the average delay and standard deviation.\n",
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"- Plot a histogram of the delays."
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]
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-11-21T08:54:21.237164Z",
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"start_time": "2025-11-21T08:54:21.222343Z"
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}
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},
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"cell_type": "code",
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"source": "serial.close()",
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"outputs": [],
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"execution_count": 55
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},
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{
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"cell_type": "code",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-11-21T09:22:30.754889Z",
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"start_time": "2025-11-21T09:22:21.720051Z"
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}
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},
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"source": [
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"### Student Version ###\n",
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"times = []\n",
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"new_times = []\n",
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"total_time = 0\n",
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"summed_times = 0\n",
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"serial = Serial('COM4', 115200)\n",
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"\n",
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"for i in range(100):\n",
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" start_time = time.time()\n",
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" serial.write(b'S\\n')\n",
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" _status = serial.read_until(b'\\x04')\n",
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" _status = _status.decode('utf-8')\n",
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" current_time = time.time() - start_time\n",
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" times.append(current_time)\n",
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"\n",
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"serial.close()\n",
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"#print(times)\n",
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"\n",
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"for j in range(100):\n",
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" total_time += times[j]\n",
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"\n",
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"average = total_time / 100\n",
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"\n",
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"for k in range(100):\n",
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" new_times.append((times[k] - average) ** 2)\n",
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" summed_times += new_times[k]\n",
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"\n",
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"variance = summed_times / 100\n",
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"standard_deviation = (variance) ** 0.5\n",
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"\n",
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"print(f'The average time of a distance measurement is: {average:.3f} [s]')\n",
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"print(f'The standard deviantion of a distance measurement is: {standard_deviation:.3f} [s]')\n",
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"\n",
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"plt.hist(times)\n",
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"plt.show()"
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],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The average time of a distance measurement is: 0.079 [s]\n",
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"The standard deviantion of a distance measurement is: 0.035 [s]\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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],
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||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data",
|
||
"jetTransient": {
|
||
"display_id": null
|
||
}
|
||
}
|
||
],
|
||
"execution_count": 63
|
||
},
|
||
{
|
||
"metadata": {},
|
||
"cell_type": "markdown",
|
||
"source": "<font color=#6698FF> As the ultrasonic sensors refresh every 70 ms taking turns, every 140 ms will give new data. So we need to measure every 140 ms to get new data and not data stored in the buffer."
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Step 3: Using Distance Values to Model the Car\n",
|
||
"\n",
|
||
"Ultrasonic sensors are not just used for detecting obstacles; they play a crucial role in modeling the car's behavior during autonomous driving. To control the car effectively, we need to understand how it responds to drive and steering commands, similar to how a human driver knows how much acceleration or steering input affects the car's movement.\n",
|
||
"\n",
|
||
"However, while KITT doesn’t have an accelerometer to measure acceleration directly, we can use the ultrasonic sensors to estimate how the car moves over time. By measuring the distance to a cardboard-box wall, we can derive its speed and acceleration.\n",
|
||
"\n",
|
||
"#### Understanding Speed and Acceleration\n",
|
||
"\n",
|
||
"- **Velocity** is the rate of change of position over time:\n",
|
||
"\n",
|
||
" $$\n",
|
||
" v(t) = \\frac{{\\mathrm d} x}{{\\mathrm d} t}(t) \\,.\n",
|
||
" $$\n",
|
||
"\n",
|
||
"- **Acceleration** is the change in speed over time:\n",
|
||
"\n",
|
||
" $$\n",
|
||
" a(t) = \\frac{{\\mathrm d} v}{{\\mathrm d} t}(t) \\,.\n",
|
||
" $$\n",
|
||
"\n",
|
||
"Note that $x(t)$, $v(t)$ and $a(t)$ are time varying. To implement the differentials, in practice we will subtract two subsequent samples $x(t_1)$ and $x(t_2)$. We will then have an estimate of $v(t)$ for $t = (t_1+t_2)/2$:\n",
|
||
"\n",
|
||
"$$\n",
|
||
"v\\left(\\frac{t_1+t_2}{2}\\right) \\approx \\frac{x(t_2) - x(t_1)}{t_2-t_1} \\,.\n",
|
||
"$$\n",
|
||
"\n",
|
||
"In theory, this approximation gets better for $t_2$ close to $t_1$, but at the same time the division of two small numbers will make the result very sensitive to noise, so in practice there is a trade-off.\n",
|
||
"\n",
|
||
"#### Plotting KITT's Motion Towards a Wall\n",
|
||
"\n",
|
||
"To understand how KITT moves, make recordings of the distance sensor values as KITT drives towards a wall. Do this for multiple motor commands, and store them in a `.csv` file. (You can use the `Files/Recordings` folder to organize your data). You can then later import the data into Python. Next to the sensor values, you should also store the time stamp of each sample.\n",
|
||
"\n",
|
||
"You will see KITT speed up, and then reach a constant speed. To do this experiment, please let KITT drive towards the supplied cardboard wall. **Turn off KITT's motors once the distance is less than 40 cm to ensure KITT does not crash into the wall.** Note that you may have to discard the first few readings as they may be inaccurate.\n",
|
||
"\n",
|
||
"*Hints:*\n",
|
||
"\n",
|
||
"- Choose an appropriate motor speed value for `motor_speed_value`.\n",
|
||
"- Ensure that you stop the car if it gets too close to the wall to prevent collisions.\n",
|
||
"- Use `time.time()` to keep track of elapsed time.\n",
|
||
"- Store the data in a list with the format `[current_time, dist_L, dist_R]`.\n",
|
||
"- Write the data to a CSV file for later analysis.\n",
|
||
"- Also document the motor speed setting (e.g. use this as part of your file name)."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-11-21T11:13:56.871532Z",
|
||
"start_time": "2025-11-21T11:13:52.882260Z"
|
||
}
|
||
},
|
||
"source": [
|
||
"### Student Version ###\n",
|
||
"from pathlib import Path\n",
|
||
"\n",
|
||
"serial = Serial('/dev/rfcomm3', 115200)\n",
|
||
"serial.write(b'D150\\n')\n",
|
||
"serial.write(b'M165\\n')\n",
|
||
"\n",
|
||
"# Initialize a list to store recorded data\n",
|
||
"data = []\n",
|
||
"\n",
|
||
"# Record data for a specified duration (e.g., 10 seconds)\n",
|
||
"recording_duration = 10 # in seconds\n",
|
||
"start_time = time.time()\n",
|
||
"\n",
|
||
"while time.time() - start_time < recording_duration:\n",
|
||
" # Send the status command to get the distance readings\n",
|
||
" serial.write(b'S\\n')\n",
|
||
" \n",
|
||
" # Read the status response\n",
|
||
" status = serial.read_until(b'\\x04').decode('utf-8')\n",
|
||
" \n",
|
||
" dist_L = None\n",
|
||
" dist_R = None\n",
|
||
"\n",
|
||
" lines = status.splitlines()\n",
|
||
"\n",
|
||
" for line in lines:\n",
|
||
" if \"Dist.\" in line:\n",
|
||
" words = line.split()\n",
|
||
" # Extract distance values based on their positions\n",
|
||
"\n",
|
||
" # Assign dist_L and dist_R accordingly\n",
|
||
" dist_L = int(words[3])\n",
|
||
" dist_R = int(words[5])\n",
|
||
" break\n",
|
||
"\n",
|
||
" current_time = time.time() - start_time\n",
|
||
" data.append([current_time, dist_L, dist_R])\n",
|
||
" \n",
|
||
" # Check if KITT is too close to the wall and stop if necessary\n",
|
||
" if dist_L < 130 or dist_R < 130:\n",
|
||
" serial.write(b'M135\\n')\n",
|
||
" time.sleep(0.75)\n",
|
||
" serial.write(b'M150\\n') # Stop the car\n",
|
||
" print(\"Stopping KITT to avoid collision.\")\n",
|
||
" break # Exit the loop\n",
|
||
" # Note: you can also add a small loop here and still read the stopping data\n",
|
||
" \n",
|
||
" time.sleep(0.1) # Wait before the next reading\n",
|
||
"\n",
|
||
"# Close the serial connection\n",
|
||
"serial.close()\n",
|
||
"\n",
|
||
"filepath = Path('./kitt_wall_data_165.csv')\n",
|
||
"df = pd.DataFrame(data,columns = [\"Time\",\"Distance_L\",\"Distance_R\"])\n",
|
||
"df.to_csv(filepath,index=False)\n",
|
||
"!pwd\n",
|
||
"# Recommeded file output: Files/Recordings/kitt_distance_data_{speed}.csv"
|
||
],
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Stopping KITT to avoid collision.\n",
|
||
"/home/nano/Documents/EE/Y2/IP3/A.K.03/Manual\r\n"
|
||
]
|
||
}
|
||
],
|
||
"execution_count": 17
|
||
},
|
||
{
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-11-21T11:12:41.634004Z",
|
||
"start_time": "2025-11-21T11:12:41.624576Z"
|
||
}
|
||
},
|
||
"cell_type": "code",
|
||
"source": "df.to_csv(Path(\"./kitt_wall_data_165.csv\"))",
|
||
"outputs": [],
|
||
"execution_count": 16
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Processing the Recorded Data\n",
|
||
"\n",
|
||
"Read your `.csv` data into Python (see template script below), and plot the distance values over time to visualize KITT's motion. Use a single plot with separate colors for the L and R sensors. You should notice a 'staircase' shape! Explain this in your report.\n",
|
||
"\n",
|
||
"Next, to derive velocity, first merge the L and R sensor data into a single position estimate: remove the duplicate values (keep only the first value of a duplicate reading), then merge the remaining values into a single (time, position) array. Plot the result in your distance plot to see if you did this correctly.\n",
|
||
"\n",
|
||
"After that, estimate the velocity of KITT as function of time. Obviously, you will use $ v(t) = \\Delta x / \\Delta t \\ $, but what time $t$ do you associate with each of these estimates?\n",
|
||
"\n",
|
||
"Make a plot of the resulting velocity estimates over time.\n",
|
||
"\n",
|
||
"*Hints:*\n",
|
||
"\n",
|
||
"- When merging the L and R distance measurements, don't simply average them. Read the above paragraph again.\n",
|
||
"- Be aware that the sensors alternate readings every 70 ms, leading to a 'staircase' effect.\n",
|
||
"- To calculate velocity, use the differences in distance and time (`diff()` function).\n",
|
||
"- Since KITT is moving towards the wall, the distance decreases; yet, the estimated velocity should be positive when moving forward.\n",
|
||
"- For the time associated with each velocity estimate, use the midpoint between consecutive time stamps.\n",
|
||
"- Remove any NaN values resulting from the `diff()` operation."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-11-26T14:37:36.226400Z",
|
||
"start_time": "2025-11-26T14:37:33.263943Z"
|
||
}
|
||
},
|
||
"source": [
|
||
"### Student Version ###\n",
|
||
"\n",
|
||
"motor_speed_value = 160 # Use the same motor speed as during recording\n",
|
||
"\n",
|
||
"# Load the recorded data from the CSV file\n",
|
||
"csv_filename = f'./kitt_wall_data_160.csv'\n",
|
||
"data = pd.read_csv(csv_filename)\n",
|
||
"\n",
|
||
"# Consider discarding the first few readings (inaccurate readings)\n",
|
||
"data = data[2:]\n",
|
||
"\n",
|
||
"# Create a new DataFrame to hold your processed data\n",
|
||
"merged_data = []\n",
|
||
"plotting_data = []\n",
|
||
"\n",
|
||
"# Iterate over the data\n",
|
||
"for index, row in data.iterrows():\n",
|
||
" # Extract time and distances\n",
|
||
" time_stamp = row['Time']\n",
|
||
" dist_L = row['Distance_L']\n",
|
||
" dist_R = row['Distance_R']\n",
|
||
" \n",
|
||
" distance = min(dist_L,dist_R)\n",
|
||
"\n",
|
||
" merged_data.append([time_stamp, distance])\n",
|
||
" plotting_data.append([time_stamp, dist_L, dist_R])\n",
|
||
"\n",
|
||
"# Convert merged data to DataFrame\n",
|
||
"merged_df = pd.DataFrame(merged_data, columns=['Time', 'Distance'])\n",
|
||
"plotting_df = pd.DataFrame(plotting_data, columns=['Time', 'Dist_L', 'Dist_R'])\n",
|
||
"\n",
|
||
"# Plotting the distance measured by the left and the right sensor\n",
|
||
"plt.figure()\n",
|
||
"plt.plot(plotting_df['Time'], plotting_df['Dist_L'], color='blue', label='Left sensor')\n",
|
||
"plt.plot(plotting_df['Time'], plotting_df['Dist_R'], color='red', label='Right sensor')\n",
|
||
"plt.xlabel('Time (s)')\n",
|
||
"plt.ylabel('Distance (cm)')\n",
|
||
"plt.title('Distance from the left and right sensor')\n",
|
||
"plt.grid(True)\n",
|
||
"plt.legend()\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"merged_df['Velocity'] = -merged_df['Distance'].diff().div(merged_df['Time'].diff())\n",
|
||
"\n",
|
||
"# Note: Use a negative sign because distance to the wall decreases as KITT moves forward\n",
|
||
"\n",
|
||
"# Calculate the time corresponding to each velocity estimate\n",
|
||
"# It's common to use the midpoint of the time intervals\n",
|
||
"merged_df['Velocity_Time'] = merged_df['Time'] - merged_df['Time'].diff() / 2\n",
|
||
"\n",
|
||
"# Plotting Distance\n",
|
||
"plt.figure()\n",
|
||
"plt.plot(merged_df['Time'], merged_df['Distance'], label='Distance to Wall')\n",
|
||
"plt.xlabel('Time (s)')\n",
|
||
"plt.ylabel('Distance (cm)')\n",
|
||
"plt.title('Distance to Wall Over Time')\n",
|
||
"plt.grid(True)\n",
|
||
"plt.legend()\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# Plotting Velocity\n",
|
||
"plt.figure()\n",
|
||
"plt.plot(merged_df['Velocity_Time'], merged_df['Velocity'], label='Velocity (cm/s)')\n",
|
||
"plt.xlabel('Time (s)')\n",
|
||
"plt.ylabel('Velocity (cm/s)')\n",
|
||
"plt.title('Velocity of KITT Over Time')\n",
|
||
"plt.grid(True)\n",
|
||
"plt.legend()\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"print(merged_df)"
|
||
],
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
],
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data",
|
||
"jetTransient": {
|
||
"display_id": null
|
||
}
|
||
},
|
||
{
|
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"data": {
|
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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
|
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],
|
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"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data",
|
||
"jetTransient": {
|
||
"display_id": null
|
||
}
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
],
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data",
|
||
"jetTransient": {
|
||
"display_id": null
|
||
}
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" Time Distance Velocity Velocity_Time\n",
|
||
"0 0.666117 291.0 NaN NaN\n",
|
||
"1 0.837830 288.0 17.471025 0.751974\n",
|
||
"2 1.030023 283.0 26.015511 0.933927\n",
|
||
"3 1.207749 276.0 39.386623 1.118886\n",
|
||
"4 1.390952 267.0 49.125710 1.299350\n",
|
||
"5 1.591268 257.0 49.921077 1.491110\n",
|
||
"6 1.790691 253.0 20.057907 1.690980\n",
|
||
"7 1.991666 240.0 64.684758 1.891178\n",
|
||
"8 2.179857 226.0 74.392436 2.085761\n",
|
||
"9 2.338029 213.0 82.188818 2.258943\n",
|
||
"10 2.515954 198.0 84.305133 2.426992\n",
|
||
"11 2.714974 190.0 40.196935 2.615464\n",
|
||
"12 2.902802 174.0 85.184397 2.808888\n",
|
||
"13 3.096991 157.0 87.543546 2.999897\n",
|
||
"14 3.247902 140.0 112.649286 3.172447\n",
|
||
"15 3.460058 122.0 84.843396 3.353980\n",
|
||
"16 3.627290 103.0 113.614594 3.543674\n",
|
||
"17 3.832908 84.0 92.404083 3.730099\n"
|
||
]
|
||
}
|
||
],
|
||
"execution_count": 40
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"**Tips to Consider:**\n",
|
||
"\n",
|
||
"**Continuous Measurement** involves data that can be taken at any point in time, with no gaps. For example, a car’s speedometer provides a continuous record of the car’s speed.\n",
|
||
"\n",
|
||
"**Discrete Measurement**, on the other hand, collects data at specific intervals. For instance, KITT’s ultrasonic sensors take distance readings every 70 ms. In between these measurements, we don’t know the exact position of the car. Discrete data can still be useful, but it may miss details about rapid changes in speed or acceleration that occur between measurements. In order to interpret it correctly, you may need to filter or interpolate the data.\n",
|
||
"\n",
|
||
"The following shows the difference between continuous and discrete data:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-11-26T13:55:32.596911Z",
|
||
"start_time": "2025-11-26T13:55:31.928370Z"
|
||
}
|
||
},
|
||
"source": [
|
||
"# Define time for continuous measurement (smooth, no gaps)\n",
|
||
"time_continuous = np.linspace(0, 10, 1000) # Time from 0 to 10 seconds, 1000 data points\n",
|
||
"# Define time for discrete measurement (specific intervals)\n",
|
||
"time_discrete = np.linspace(0, 10, 20) # Time from 0 to 10 seconds, 20 data points\n",
|
||
"# Simulate continuous speed (sinusoidal speed pattern for illustration)\n",
|
||
"speed_continuous = 10 * np.sin(0.5 * np.pi * time_continuous) # Continuous speed\n",
|
||
"# Simulate discrete speed (sampled at specific intervals)\n",
|
||
"speed_discrete = 10 * np.sin(0.5 * np.pi * time_discrete) # Discrete speed\n",
|
||
"# Plotting both continuous and discrete measurements\n",
|
||
"plt.figure(figsize=(7, 4))\n",
|
||
"plt.plot(time_continuous, speed_continuous, label=\"Continuous Measurement\", color=\"blue\")\n",
|
||
"plt.scatter(time_discrete, speed_discrete, label=\"Discrete Measurement\", color=\"red\", zorder=5)\n",
|
||
"plt.xlabel('Time (s)')\n",
|
||
"plt.ylabel('Speed (cm/s)')\n",
|
||
"plt.title('Continuous vs Discrete Measurement of Speed')\n",
|
||
"plt.legend()\n",
|
||
"plt.grid(True)\n",
|
||
"plt.show()"
|
||
],
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<Figure size 700x400 with 1 Axes>"
|
||
],
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data",
|
||
"jetTransient": {
|
||
"display_id": null
|
||
}
|
||
}
|
||
],
|
||
"execution_count": 38
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Step 5: Implementing the Distance Sensor Reading in Your KITT Class\n",
|
||
"\n",
|
||
"In the previous module, you have created a class for KITT. Add a method to read the distance sensors to your `KITT` class in your 'Student Code' files. You can use the code you have written in the previous steps to do this. Make sure to test your code. It is advisable to store all the old distance data in a list inside the `KITT` class. This will be convenient during the final challenge, where the route planning might need old measurements to determine the position of objects.\n",
|
||
"\n",
|
||
"**Student Task:**\n",
|
||
"\n",
|
||
"- Add a method `read_distance_sensors()` to your `KITT` class.\n",
|
||
"- The method should send the status command to KITT and extract the distance measurements.\n",
|
||
"- Store the readings along with timestamps in an internal list or data structure.\n",
|
||
"\n",
|
||
"### Step 6: Mid-term Assessment 2.1 and Report\n",
|
||
"\n",
|
||
"After you finish this assignment, and ultimately in week 4, showcase the functionality of your script to your assigned TA. After you pass this assessment, you are ready to document your results in your midterm report. For this Module, you would include a chapter that covers the above tasks (using independently-readable text, i.e., don’t refer to “Step 1”).\n",
|
||
"\n",
|
||
"Include plots; for each plot, it should be clear how the plot was made (i.e., the corresponding experimental setup), and you have to describe what is seen in the plot before you discuss results and derive conclusions. Review the guidelines in Chapter 7 for more information. Include the corresponding code in an appendix.\n",
|
||
"\n",
|
||
"Remember to document your code, using comments to define input/output variables of functions and to explain the logic and any modifications made. Your completed script will be crucial for the upcoming challenges, contributing to the overall autonomous driving system."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## The Microphones\n",
|
||
"\n",
|
||
"The field is equipped with four microphones at its corners, and a fifth microphone positioned at a higher level between two of the edge microphones. These microphones, together with the beacon mounted on KITT, will be used to locate KITT within the field (more details in Chapter 5).\n",
|
||
"\n",
|
||
"<img src=\"pictures/axisdef.png\" alt=\"Microphones Axis Defenition\" width=\"400\" height=\"240\">\n",
|
||
"\n",
|
||
"To use the microphone array, you must ensure that the correct sound card driver is installed. The sound card used in this project is the **Scarlett 18i20 3rd Gen**. Below are instructions on how to configure Sounddevice and the necessary drivers on different platforms.\n",
|
||
"\n",
|
||
"### Simulator\n",
|
||
"For the Sounddevice package another simulator has been made. The simulator will return a realistic audio recording, and change the recordings according to the location of the car. But, it contains only 1 recording, so it will not appear as random as the real car. It also does not adjust to your particular beacon settings. Make sure to test on the real car frequently. Use it in combination with the serial simulator to change locations and test like you would on the real car.\n",
|
||
"\n",
|
||
"### Important: Lab rules for the microphone array\n",
|
||
"\n",
|
||
"When working with the microphone array, please follow these rules to ensure smooth operations and avoid disrupting other groups:\n",
|
||
"\n",
|
||
"1. **Do not rearrange the microphone connectors**. The setup is shared between multiple groups, and changing the connections may lead to incorrect results for other teams.\n",
|
||
"2. **Do not touch the volume settings**. If the volume needs adjustment, contact a TA for assistance.\n",
|
||
"3. **Handle the equipment carefully**. The microphone array and associated hardware are sensitive, and mishandling could cause damage.\n",
|
||
"4. **Start and stop on time**. The lab is shared, and other groups have scheduled time slots. Be respectful of their time.\n",
|
||
"\n",
|
||
"Test time is limited. But by using the simulator and preparing a plan of what you want to test during each scheduled slot, there should be enough time to complete the tasks. \n",
|
||
"\n",
|
||
"### Step 1: Initializing the microphone array\n",
|
||
"\n",
|
||
"Before using the microphone array, it must first be initialized. As part of the initialization process, you will need to specify the sampling frequency (`Fs`) that will be used to record the audio. The sampling frequency will vary based on the test field you are working with, and it will be **48 kHz** or **44.1 kHz**.\n",
|
||
"\n",
|
||
"A typical laptop or PC may have multiple audio devices (e.g., built-in microphones, Bluetooth headsets, external sound cards). To ensure that the correct device is used, you can list all available audio devices using Sounddevice and select the appropriate one. Use the following code snippet to list all audio devices recognized by Sounddevice and find the index of the Scarlett 18i20 or any other relevant device:"
|
||
]
|
||
},
|
||
{
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-11-28T10:46:33.709684Z",
|
||
"start_time": "2025-11-28T10:46:33.704506Z"
|
||
}
|
||
},
|
||
"cell_type": "code",
|
||
"source": [
|
||
"for i, device in enumerate(sounddevice.query_devices()):\n",
|
||
" print(i, device['name'])"
|
||
],
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"0 HDA Intel PCH: ALC3204 Analog (hw:0,0)\n",
|
||
"1 HDA Intel PCH: HDMI 0 (hw:0,3)\n",
|
||
"2 HDA Intel PCH: HDMI 1 (hw:0,7)\n",
|
||
"3 HDA Intel PCH: HDMI 2 (hw:0,8)\n",
|
||
"4 HDA Intel PCH: HDMI 3 (hw:0,9)\n",
|
||
"5 Scarlett 18i20 USB: Audio (hw:1,0)\n",
|
||
"6 sysdefault\n",
|
||
"7 front\n",
|
||
"8 surround40\n",
|
||
"9 surround51\n",
|
||
"10 surround71\n",
|
||
"11 hdmi\n",
|
||
"12 pipewire\n",
|
||
"13 dmix\n",
|
||
"14 default\n",
|
||
"15 Scarlett 18i20 3rd Gen Direct Scarlett 18i20 USB\n",
|
||
"16 Built-in Audio Analog Stereo\n"
|
||
]
|
||
}
|
||
],
|
||
"execution_count": 62
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Step 2: Recording audio data\n",
|
||
"\n",
|
||
"To make a recording with the microphone array, you must specify the **length of the recording** as the number of **audio frames** to capture. Each audio frame consists of samples from all 5 microphones. Given that we are using 16-bit audio (2 bytes per sample), each frame will contain **10 bytes** (5 microphones × 2 bytes per sample).\n",
|
||
"\n",
|
||
"Thus, recording **N frames** will produce **10N bytes** of data. Note: The simulator returns a fixed length recording at 44.1 kHz. The real car will return a recording of the length you specify.\n",
|
||
"\n",
|
||
"The following command records `N` frames from the microphone array and stores the result as a numpy array:"
|
||
]
|
||
},
|
||
{
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-11-28T10:46:45.691740Z",
|
||
"start_time": "2025-11-28T10:46:40.233014Z"
|
||
}
|
||
},
|
||
"cell_type": "code",
|
||
"source": [
|
||
"Fs = 48000\n",
|
||
"duration = 5\n",
|
||
"N = int(Fs * duration)\n",
|
||
"\n",
|
||
"sounddevice.default.device = 15 # or a substring of its name\n",
|
||
"sounddevice.default.samplerate = Fs\n",
|
||
"\n",
|
||
"samples = sounddevice.rec(N, samplerate=Fs, channels=5)\n",
|
||
"sounddevice.wait()\n",
|
||
"print(samples.shape)"
|
||
],
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"(240000, 5)\n"
|
||
]
|
||
}
|
||
],
|
||
"execution_count": 63
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Plotting the audio data\n",
|
||
"\n",
|
||
"Once you've extracted the audio data for each microphone, you can plot it using Python. **Matplotlib** is a commonly used module for creating plots. Plot the audio data from each microphone to visualize the sound captured by the microphone array:"
|
||
]
|
||
},
|
||
{
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-11-28T10:48:46.078083Z",
|
||
"start_time": "2025-11-28T10:48:42.998670Z"
|
||
}
|
||
},
|
||
"cell_type": "code",
|
||
"source": [
|
||
"### Student Version ###\n",
|
||
"samples_reshaped = np.array(samples)\n",
|
||
"fig, ax = plt.subplots(5,1,figsize=(20,30))\n",
|
||
"\n",
|
||
"t = np.arange(0,N/Fs,1/Fs)\n",
|
||
"ax[0].plot(t,samples_reshaped[:,0])\n",
|
||
"ax[1].plot(t,samples_reshaped[:,1])\n",
|
||
"ax[2].plot(t,samples_reshaped[:,2])\n",
|
||
"ax[3].plot(t,samples_reshaped[:,3])\n",
|
||
"ax[4].plot(t,samples_reshaped[:,4])\n",
|
||
"for i,ax_in in enumerate(ax):\n",
|
||
" ax_in.set_xlabel('Time (s)')\n",
|
||
" ax_in.set_ylabel('Amplitude')\n",
|
||
" ax_in.set_title(f'Mic {i}')\n",
|
||
"fig.show()\n",
|
||
"\n",
|
||
"from scipy.io import wavfile\n",
|
||
"wavfile.write(\"./audio_beacon_67676767_at_x345_y101.wav\", Fs, samples_reshaped.astype(np.float32))"
|
||
],
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/tmp/ipykernel_5220/2185087391.py:15: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
|
||
" fig.show()\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<Figure size 2000x3000 with 5 Axes>"
|
||
],
|
||
"image/png": 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|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data",
|
||
"jetTransient": {
|
||
"display_id": null
|
||
}
|
||
}
|
||
],
|
||
"execution_count": 64
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Step 3: Testing the microphone array\n",
|
||
"Below are some experiments you can perform to test the microphone array, and develop the code.\n",
|
||
"\n",
|
||
"**Part 1: Clapping**: With the real microphones connected, have your teammate clap in front of each microphone in turn. Record the audio data and plot the results. Is the order of the microphones what you expected? How does the sound intensity change as you move from one microphone to another?\n",
|
||
"\n",
|
||
"**Part 2: Beacon detection**: Turn on KITT's beacon and record the results. Can you identify where KITT is located just by observing the shift in the recordings? Change the beacons parameters and see how it affects the recordings.\n",
|
||
"\n",
|
||
"**Part 3: Ideal OOK signal**: Compare the waveform of the recording to an ideal OOK of your code. What can you see, and what do you infer from this? Are some beacon signals better than others? How can you find a good beacon signal? (This point is revisited in Module 3.)\n",
|
||
"\n",
|
||
"**Part 4: Reference recording**: Make some recordings of the beacon at different locations. These recordings will be useful to your teammates working on the localization algorithm. Similarly, make a recording of a single pulse from the beacon close to one of the microphones. Cut out the pulse and save it separately.\n",
|
||
"\n",
|
||
"**Part 5: KITT class**: Add a method to read the microphones to your KITT class in 'Student Code' files. The method should make a stream, turn on the beacon, start the recording, stop the recording, and turn off the beacon. You can choose to return the recording as a result, or store it internally inside the KITT class. Make sure to test your code."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"*Bonus Tasks - Optional*\n",
|
||
"\n",
|
||
"- See if you can automate selecting the correct sounddevice device index. The correct device index changes from one computer to another and can sometimes even change on the same computer after a reboot. So, it is worth your time to make a program that can automatically select the right device index.\n",
|
||
"- Implement start-up sanity checks: some process which you can run after you arrive at the test field, so that you can quickly check the microphone connections and audio levels.\n",
|
||
"\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Mid-term assessment 2.2 and report\n",
|
||
"\n",
|
||
"After you finish this assignment, and ultimo in week 4, showcase the functionality of your script to your\n",
|
||
"assigned TA. After you pass this assessment, you are ready to document your results in your midterm\n",
|
||
"report.\n",
|
||
"\n",
|
||
"For this Module, you would include a chapter that covers the above tasks (using independently-readable\n",
|
||
"text, i.e., don’t refer to “Task 1”). Include plots; for each plot it should be clear how the plot was made\n",
|
||
"(i.e., the corresponding experimental set-up), and you have to describe what is seen in the plot before\n",
|
||
"you discuss results and derive any conclusions. Be sure to answer the questions posed along with the\n",
|
||
"plots (using independently-readable text).\n",
|
||
"\n",
|
||
"Include the corresponding code in an Appendix. Remember to document your code, using comments\n",
|
||
"to define input/output variables of functions and to explain the logic and any modifications made. Your\n",
|
||
"completed script will be crucial for the upcoming challenges, contributing to the overall autonomous\n",
|
||
"driving system.\n",
|
||
"\n",
|
||
"This concludes the mid-term assignments related to communication with KITT. After the mid-term, you\n",
|
||
"must integrate this module with the localization module created by your colleagues. Take into account\n",
|
||
"that integrating is often harder than originally anticipated, e.g. your code has to run in parallel, and you\n",
|
||
"have to worry about timing aspects. Hopefully, using the KITT class will provide you with a sturdy and\n",
|
||
"flexible framework to continue your work towards the final challenge\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## FAQ\n",
|
||
"\n",
|
||
"**What is the beam angle ?**\n",
|
||
"\n",
|
||
"The beam angle of a sensor refers to how wide the sensor's detection area is. It determines how much space the sensor can cover when it sends out signals (like sound or light) to detect objects.\n",
|
||
"\n",
|
||
"To determine the beam angle of ultrasonic sensors mounted in front of the car, you have multiple options: \n",
|
||
"\n",
|
||
"1. **Check the sensor datasheet**: The easiest way or at least a way to get some idea to determine the beam angle is to refer to the manufacturer's datasheet for your specific ultrasonic sensor. The datasheet will typically provide the beam angle, often around 15 to 30 degrees for common ultrasonic sensors. But keep in mind that is for a single sensor and not the current set up! Also, the 'reach' of the sensor is angle dependent: straight ahead, it can see several meters, but at an angle, perhaps just half a meter. \n",
|
||
"\n",
|
||
"2. **Experimental Determination for KITT**:\n",
|
||
" - **Measure detection width**: Place a flat object (like a wall) at a fixed distance in front of the sensor (e.g., 1 meter).\n",
|
||
" - **Move the object**: Move the object left and right to determine the points where the sensor stops detecting the object.\n",
|
||
" - **Calculate the angle**: Measure the distance between these two points (detection width) and the distance from the sensor to the object. You may use the following formula:\n",
|
||
"\n",
|
||
" \n",
|
||
" $$\n",
|
||
" \\text{Beam Angle} = 2 \\times \\arctan\\left(\\frac{\\text{Detection Width}/2}{\\text{Distance to Object}}\\right)$$\n",
|
||
" \n",
|
||
" - This calculation will give you the beam angle in degrees.\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"**I see random numbers from sensors for large distances. Is my sensor damaged ?**\n",
|
||
"\n",
|
||
"During experiments, you may occasionally receive random or unexpected data from the sensors. This can occur not only when the sensors are operating outside their effective range but also at times when they are within range. Several factors (consider what they might be?) can cause ultrasonic sensors to produce inaccurate readings. Additionally, since there are two sensors—one on the left and one on the right—they might produce different, completly different readings.\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"**Are the ultrasonic sensor measurements for the left and the right side done at exactly the same time ?**\n",
|
||
"\n",
|
||
"If you closely observe the blinking of the small LEDs on the ultrasonic board on the car, you might notice that they turn on and off alternatingly. This indicates a slight time difference in the sensor measurements. This delay is also noticeable and can be measured using a moving car. (The reason to operate the two sensors alternatingly is that otherwise they might interfere on each other.)"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
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|
||
"display_name": "Python 3",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
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|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.13.3"
|
||
}
|
||
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|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
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