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hybrid_breadth_first.cpp
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#include <algorithm>
#include <iostream>
#include <sstream>
#include <fstream>
#define _USE_MATH_DEFINES
#include <cmath>
#include <math.h>
#include <vector>
#include "hybrid_breadth_first.h"
using namespace std;
HBF::HBF() {
}
HBF::~HBF() {
}
bool HBF::compare_maze_s(const HBF::maze_s &lhs, const HBF::maze_s &rhs) {
return lhs.f < rhs.f;
}
double HBF::heuristic(double x, double y, vector<int> goal) {
return fabs(y - goal[0]) + fabs(x - goal[1]);
}
int HBF::theta_to_stack_number(double theta) {
double new_theta = fmod((theta + 2 * M_PI), (2 * M_PI));
int stack_number = (int)(round(new_theta*NUM_THETA_CELLS / (2 * M_PI))) % NUM_THETA_CELLS;
return stack_number;
}
int HBF::idx(double float_num) {
return int(floor(float_num));
}
vector<HBF::maze_s> HBF::expand(HBF::maze_s state, vector<int> goal) {
int g = state.g;
double x = state.x;
double y = state.y;
double theta = state.theta;
int g2 = g + 1;
vector<HBF::maze_s> next_states;
for (double delta_i = -35; delta_i < 40; delta_i+=5) {
double delta = (M_PI / 180)*delta_i;
double omega = (SPEED / LENGTH)*tan(delta);
double theta2 = theta + omega;
if (theta2 < 0) {
theta2 += 2 * M_PI;
}
double x2 = x + SPEED*cos(theta);
double y2 = y + SPEED*sin(theta);
HBF::maze_s state2;
state2.f = g2 + heuristic(x2, y2, goal);
state2.g = g2;
state2.x = x2;
state2.y = y2;
state2.theta = theta2;
next_states.push_back(state2);
}
return next_states;
}
vector<HBF::maze_s> HBF::reconstruct_path(vector<vector<vector<HBF::maze_s>>> came_from, vector<double> start, HBF::maze_s final) {
vector<maze_s> path = { final };
int stack_no = theta_to_stack_number(final.theta);
maze_s current = came_from[stack_no][idx(final.x)][idx(final.y)];
int stack = theta_to_stack_number(current.theta);
double x = current.x;
double y = current.y;
while (x != start[0] || y != start[1]) {
path.push_back(current);
current = came_from[stack][idx(x)][idx(y)];
x = current.x;
y = current.y;
stack = theta_to_stack_number(current.theta);
}
return path;
}
HBF::maze_path HBF::search(vector< vector<int> > grid, vector<double> start, vector<int> goal) {
/*
Working Implementation of breadth first search. Does NOT use a heuristic
and as a result this is pretty inefficient. Try modifying this algorithm
into hybrid A* by adding heuristics appropriately.
*/
vector< vector< vector<int> > > closed(NUM_THETA_CELLS, vector<vector<int>>(grid[0].size(), vector<int>(grid.size())));
vector< vector< vector<maze_s> > > came_from(NUM_THETA_CELLS, vector<vector<maze_s>>(grid[0].size(), vector<maze_s>(grid.size())));
double theta = start[2];
int stack = theta_to_stack_number(theta);
int g = 0;
maze_s state;
state.g = g;
state.x = start[0];
state.y = start[1];
state.f = g + heuristic(state.x, state.y, goal);
state.theta = theta;
closed[stack][idx(state.x)][idx(state.y)] = 1;
came_from[stack][idx(state.x)][idx(state.y)] = state;
int total_closed = 1;
vector<maze_s> opened = { state };
bool finished = false;
while (!opened.empty())
{
sort(opened.begin(), opened.end(), compare_maze_s);
maze_s next = opened[0]; //grab first elment
opened.erase(opened.begin()); //pop first element
int x = next.x;
int y = next.y;
if (idx(x) == goal[0] && idx(y) == goal[1])
{
cout << "found path to goal in " << total_closed << " expansions" << endl;
maze_path path;
path.came_from = came_from;
path.closed = closed;
path.final = next;
return path;
}
vector<maze_s> next_state = expand(next, goal);
for (int i = 0; i < next_state.size(); i++)
{
int g2 = next_state[i].g;
double x2 = next_state[i].x;
double y2 = next_state[i].y;
double theta2 = next_state[i].theta;
if ((x2 < 0 || x2 >= grid.size()) || (y2 < 0 || y2 >= grid[0].size()))
{
//invalid cell
continue;
}
int stack2 = theta_to_stack_number(theta2);
if (closed[stack2][idx(x2)][idx(y2)] == 0 && grid[idx(x2)][idx(y2)] == 0)
{
opened.push_back(next_state[i]);
closed[stack2][idx(x2)][idx(y2)] = 1;
came_from[stack2][idx(x2)][idx(y2)] = next;
total_closed += 1;
}
}
}
cout << "no valid path." << endl;
HBF::maze_path path;
path.came_from = came_from;
path.closed = closed;
path.final = state;
return path;
}