mirror of
https://gitlab.ewi.tudelft.nl/ee2l1/2025-2026/A.K.03.git
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Functioning distance extraction code
# Conflicts: # Manual/4_Module_2.ipynb
This commit is contained in:
Thijs Driessen
Nicholas Stănescu
parent
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commit
1a9b6bbf33
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{
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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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"cell_type": "markdown",
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"source": [
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"\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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"execution_count": null,
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": [
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"# Import necessary libraries\n",
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"import time\n",
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@ -32,18 +32,19 @@
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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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"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 Manual.KITT_Simulator.sounddevice_simulator import sounddevice\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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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"cell_type": "markdown",
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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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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"## Distance Sensors\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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"execution_count": null,
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": [
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"### Student Version ###\n",
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"\n",
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"# TODO: Establish a serial connection, ask for a status report, read it out, and print it\n",
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"serial = Serial('/dev/rfcomm2', 115200)\n",
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"serial.write(b'S\\n')\n",
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"status = serial.read_until(b'\\n')\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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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": "serial.close()"
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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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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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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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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" # TODO: Decode the status response to a string\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'\\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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" # TODO: Split the status string into lines\n",
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" for line in lines:\n",
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" if \"Dist.\" in line:\n",
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" # TODO: Split the line into words\n",
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" words = lines.split()\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 =\n",
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" dist_R =\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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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": "extract_dis()"
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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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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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"source": [
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"### Student Version ###\n"
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]
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"execution_count": null,
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"source": "### Student Version ###\n"
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"### Step 3: Using Distance Values to Model the Car\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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"execution_count": null,
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": [
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"### Student Version ###\n",
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"\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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"cell_type": "markdown",
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"source": [
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"#### Processing the Recorded Data\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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"execution_count": null,
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": [
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"### Student Version ###\n",
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"\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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"cell_type": "markdown",
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"source": [
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"**Tips to Consider:**\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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"execution_count": null,
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": [
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"# Define time for continuous measurement (smooth, no gaps)\n",
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"time_continuous = np.linspace(0, 10, 1000) # Time from 0 to 10 seconds, 1000 data points\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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"cell_type": "markdown",
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"source": [
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"### Step 5: Implementing the Distance Sensor Reading in Your KITT Class\n",
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"\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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"cell_type": "markdown",
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"source": [
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"## The Microphones\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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"execution_count": null,
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": [
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"sounddevice_handle = sounddevice()\n",
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"for i in range(sounddevice_handle.get_device_count()):\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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"cell_type": "markdown",
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"source": [
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"Once you have identified the index of the microphone array device from the list, you can initialize it by specifying the device index (`device_index`) and the desired sampling frequency (`Fs`).\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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"execution_count": null,
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": [
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"# Initialize sounddevice again\n",
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"sounddevice_handle = sounddevice()\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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"cell_type": "markdown",
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"source": [
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"### Step 2: Recording audio data\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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"execution_count": null,
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": [
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"Fs = 44100 # Sampling frequency\n",
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"N = 2*Fs # 2 seconds of audio data\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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"cell_type": "markdown",
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"source": [
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"At this point, the microphone data is **interleaved**. This means that the first value (`data[0]`) corresponds to the first sample of microphone 0, the second value (`data[1]`) corresponds to the first sample of microphone 1, and so on. For example, `data[5]` contains the second sample of microphone 0, and the pattern continues. To visualize the interleaving of the data, refer to the table below:\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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"execution_count": null,
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": [
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"### Student Version ###\n",
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"\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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"cell_type": "markdown",
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"source": [
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"### Plotting the audio data\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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"execution_count": null,
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": [
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"### Student Version ###\n",
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"\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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"cell_type": "markdown",
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"source": [
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"### Step 3: Testing the microphone array\n",
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"Below are some experiments you can perform to test the microphone array, and develop the code.\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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"cell_type": "markdown",
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"source": [
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"*Bonus Tasks - Optional*\n",
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"\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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"cell_type": "markdown",
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"source": [
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"### Mid-term assessment 2.2 and report\n",
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"\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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"cell_type": "markdown",
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"source": [
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"## 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": "markdown",
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"**I see random numbers from sensors for large distances. Is my sensor damaged ?**\n",
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"\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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"cell_type": "markdown",
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"source": [
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"**Are the ultrasonic sensor measurements for the left and the right side done at exactly the same time ?**\n",
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"\n",
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