adityakamath

#!/bin/bash

# Ref: https://github.com/J-Pai/EnvTrackerNode/tree/master

# Development setup including support for cross-compilation
# to AArch64, runtime dependencies and tools
sudo apt install python3 python3-dev python3-pip python3-venv  \
                 build-essential autoconf libtool bear         \
                 pkg-config cmake libssl-dev libsasl2-dev      \
                 openssl libcurl4-openssl-dev libc++-dev       \

adityakamath

import os
import time
import math
import RTIMU
from copy import deepcopy

class IMUSensor:
    def __init__(self, imu_settings_file='RTIMULib'):
        self._imu_settings = self._get_settings_file(imu_settings_file)
        self._imu = RTIMU.RTIMU(self._imu_settings)

adityakamath

<?xml version="1.0" encoding="UTF-8" ?>
<dds>
    <profiles xmlns="http://www.eprosima.com/XMLSchemas/fastRTPS_Profiles">
        <participant profile_name="TailscaleDiscoveryServer" is_default_profile="true">
            <rtps>
                <builtin>
                    <discovery_config>
                        <discoveryProtocol>SUPER_CLIENT</discoveryProtocol>
                        <discoveryServersList>
                            <RemoteServer prefix="44.53.00.5f.45.50.52.4f.53.49.4d.41">

adityakamath

<?xml version="1.0" encoding="UTF-8" ?>
<profiles xmlns="http://www.eprosima.com/XMLSchemas/fastRTPS_Profiles">
    <transport_descriptors>
        <transport_descriptor>
            <transport_id>TailscaleTransport</transport_id>
            <type>UDPv4</type>
        </transport_descriptor>
    </transport_descriptors>
    <participant profile_name="TailscaleSimple" is_default_profile="true">
        <rtps>

adityakamath

# Copyright 2017 Open Source Robotics Foundation, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

adityakamath

            # h = height/altitude of the sensor from ground
            # fov = field of view of the sensor in radians
            # res = resolution of the sensor in pixels
            # scaler = scaling factor
            # dt = time period of this loop
            
            conversion_factor = h*2*np.tan(fov/2)/(res*scaler)

            if 'paa5100':
                # Convert data from sensor frame to ROS frame for PAA5100

adityakamath

from launch import LaunchDescription
from launch.actions import EmitEvent, RegisterEventHandler
from launch.events import matches_action
from launch_ros.actions import LifecycleNode
from launch_ros.event_handlers import OnStateTransition
from launch_ros.events.lifecycle import ChangeState
from lifecycle_msgs.msg import Transition

def generate_launch_description():
    ld = LaunchDescription()

adityakamath

# The frequency, in Hz, at which the filter will output a position estimate. Note that the filter will not begin
# computation until it receives at least one message from one of the inputs. It will then run continuously at the
# frequency specified here, regardless of whether it receives more measurements. Defaults to 30 if unspecified.
frequency: 60

# The period, in seconds, after which we consider a sensor to have timed out. In this event, we carry out a predict
# cycle on the EKF without correcting it. This parameter can be thought of as the minimum frequency with which the
# filter will generate new output. Defaults to 1 / frequency if not specified.
sensor_timeout: 0.05

adityakamath

void potential_fields() {
	// these are the coordinates of the setpoint and the current position of the robot
	// normally xr should be zero, equal to x0 (origin right in the center of the corridor)
	// and y0 must have a value

	float theta, phi, r = 1, Fatt_x, Fatt_y, Ftot_x, Ftot_y, Frep_x = 0, Frep_y = 0, Frep = 0, xr = 0, yr = 0, xs = 0.1, ys = 0;

	Fatt_x = ws * (xs - xr);
	Fatt_y = ws * (ys - yr);

adityakamath

void adjust_LRF() {

	for (unsigned int i = 0; i < scan.ranges.size(); ++i) { // i choose 0.01 because the invalid LRF are small negative and positive values
		if (decision_variable == 1 || turning_left) { // left turn
			if (i < 350) scan.ranges[i] = block_distance; 
			else if (scan.ranges[i] < 0.01 || scan.ranges[i] > radius_value || scan.ranges[i] != scan.ranges[i]) scan.ranges[i] = radius_value; 
		}
		else if (decision_variable == 2 || turning_right) { // right turn
			if (i > 650) scan.ranges[i] = block_distance; 
			else if (scan.ranges[i] < 0.01 || scan.ranges[i] > radius_value || scan.ranges[i] != scan.ranges[i]) scan.ranges[i] = radius_value;