anasAlsalol

#!/usr/bin/env python3
"""
TurtleBot3 Obstacle Avoidance Node
Subscribes to /scan (LiDAR) and publishes to /cmd_vel
Implements: Forward movement, obstacle detection, collision avoidance
"""

import rclpy
from rclpy.node import Node
from sensor_msgs.msg import LaserScan

anasAlsalol

TurtleBot3 LIDAR Data Analysis Report

1. Executive Summary

• Robot: TurtleBot3 burger
• Data Collected: 137 scans
• Collection Duration: 30.0 seconds
• Data Quality: 100.0% valid measurements

2. Key Statistics

| Metric | Value |

anasAlsalol

anasAlsalol

anasAlsalol

anasAlsalol

https://github.com/cartertrafton/restaurant_db.git
https://drive.google.com/open?id=1ALiE7yv9sXIn9qhubtj77ThHY8N7gGBF

anasAlsalol

# import numpy
# numpy.arange(1,29)

seat = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,
        18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28]
reserved_seat = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
                 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]


def count_available_seat():

anasAlsalol

name = input("Enter file ")
handle = open("sample.txt")
counts = dict()
for line in handle:
    words = line.split()
    for word in words:
        counts[word] = counts.get(word , 0) + 1

print((v,k) for k,v in counts.items())

anasAlsalol

import math
AbnormalECG = open('AbnormalECG.txt').read().split()
ReferenceECG = open('ReferenceECG.txt').read().split()

sum = 0

for i in range(len(AbnormalECG)):
    sum = sum + float(AbnormalECG[i]) * float(ReferenceECG[i])

ex = 0

anasAlsalol

# check Reservation - recive id - read from file - if ok change other reject

# 1- init the empty file
# 2- diplay the menu
# 3- while not 5 list .
# python tcp client A

import socket
import pickle
import numpy