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<!DOCTYPE html> | |
<html> | |
<head> | |
<meta name="description" content="Chistes de Chuck Norris con RxJS"> | |
<meta charset="utf-8"> | |
<script src="https://unpkg.com/@reactivex/rxjs@5.0.3/dist/global/Rx.js"></script> | |
<meta name="viewport" content="width=device-width"> | |
<title>JS Bin</title> | |
</head> | |
<body> |
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#!/usr/bin/env python | |
import rospy | |
from std_msgs.msg import Int32 | |
from geometry_msgs.msg import Twist | |
from move_base_msgs.msg import MoveBaseAction, MoveBaseGoal | |
from pi_trees_ros.pi_trees_ros import * | |
class Patrol_tree: | |
def __init__(self): | |
rospy.init_node("patrol_tree") |
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#!/usr/bin/env python | |
import string | |
from random import random, shuffle | |
import os | |
# import pygraphviz as pgv | |
from time import sleep |
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FROM dorowu/ubuntu-desktop-lxde-vnc:bionic | |
ENV DEBIAN_FRONTEND noninteractive | |
# Setup your sources list and keys | |
RUN apt-get update && apt-get install -q -y --no-install-recommends \ | |
dirmngr \ | |
gnupg2 \ | |
lsb-release \ | |
&& rm -rf /var/lib/apt/lists/* |
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<html> | |
<head> | |
</head> | |
<body> | |
<script type="module"> | |
//Nos autentificamos y probamos a obtener la lista de la compra | |
//solo para ver qué pasa con los tokens jwt desde las herramientas de desarrollador | |
import PocketBase from "https://unpkg.com/pocketbase/dist/pocketbase.es.mjs"; |
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from scipy.stats import norm | |
import math | |
#desviación típica del sensor | |
EPSILON_ALFA = math.radians(15) | |
EPSILON_D = 0.3 | |
# calcula el valor de una gaussiana en un punto x, sup. media 0 y desv típica epsilon | |
def prob(x, epsilon): | |
return norm.pdf(x, loc=0, scale=epsilon) |
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#!/usr/bin/env python3 | |
# -*- coding: utf-8 -*- | |
""" | |
Odometry-based motion model (Probabilistic Robotics style) | |
Implements: | |
- motion_model_odometry(xp, x, u, alphas) -> likelihood p(x' | u, x) | |
- sample_motion_model_odometry(u, x, alphas, n) -> samples x' ~ p(x'|u,x) | |
- odom_from_poses(xp, x) -> (Δrot1, Δtrans, Δrot2) from two poses |
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#!/usr/bin/env python3 | |
# -*- coding: utf-8 -*- | |
""" | |
Beam range sensor — Beam Model + Likelihood Field Model (LFM) | |
- First: show the simulated occupancy map and raycasting result (z_exp). | |
- Second: plot the BEAM model mixture components and total (continuous + stem at z_max). | |
- Third: implement and plot the Likelihood Field Model curve p(z | x, m) for the same beam. | |
(Also display the distance field heatmap for intuition). |