diff --git a/PathPlanning/BidirectionalBreadthFirstSearch/bidirectional_breadth_first_search.py b/PathPlanning/BidirectionalBreadthFirstSearch/bidirectional_breadth_first_search.py new file mode 100644 index 00000000..d29112eb --- /dev/null +++ b/PathPlanning/BidirectionalBreadthFirstSearch/bidirectional_breadth_first_search.py @@ -0,0 +1,311 @@ +""" + +Bidirectional Breadth-First grid planning + +author: Erwin Lejeune (@spida_rwin) + +See Wikipedia article (https://en.wikipedia.org/wiki/Breadth-first_search) + +""" + +import math + +import matplotlib.pyplot as plt + +show_animation = True + + +class BidirectionalBreadthFirstSearchPlanner: + + def __init__(self, ox, oy, reso, rr): + """ + Initialize grid map for bfs planning + + ox: x position list of Obstacles [m] + oy: y position list of Obstacles [m] + reso: grid resolution [m] + rr: robot radius[m] + """ + + self.reso = reso + self.rr = rr + self.calc_obstacle_map(ox, oy) + self.motion = self.get_motion_model() + + class Node: + def __init__(self, x, y, cost, pind, parent): + self.x = x # index of grid + self.y = y # index of grid + self.cost = cost + self.pind = pind + self.parent = parent + + def __str__(self): + return str(self.x) + "," + str(self.y) + "," + str( + self.cost) + "," + str(self.pind) + + def planning(self, sx, sy, gx, gy): + """ + Bidirectional Breadth First search based planning + + input: + sx: start x position [m] + sy: start y position [m] + gx: goal x position [m] + gy: goal y position [m] + + output: + rx: x position list of the final path + ry: y position list of the final path + """ + + nstart = self.Node(self.calc_xyindex(sx, self.minx), + self.calc_xyindex(sy, self.miny), 0.0, -1, None) + ngoal = self.Node(self.calc_xyindex(gx, self.minx), + self.calc_xyindex(gy, self.miny), 0.0, -1, None) + + open_set_A, closed_set_A = dict(), dict() + open_set_B, closed_set_B = dict(), dict() + open_set_B[self.calc_grid_index(ngoal)] = ngoal + open_set_A[self.calc_grid_index(nstart)] = nstart + + while 1: + if len(open_set_A) == 0: + print("Open set A is empty..") + break + + if len(open_set_B) == 0: + print("Open set B is empty") + break + + current_A = open_set_A.pop(list(open_set_A.keys())[0]) + current_B = open_set_B.pop(list(open_set_B.keys())[0]) + + c_id_A = self.calc_grid_index(current_A) + c_id_B = self.calc_grid_index(current_B) + + closed_set_A[c_id_A] = current_A + closed_set_B[c_id_B] = current_B + + # show graph + if show_animation: # pragma: no cover + plt.plot(self.calc_grid_position(current_A.x, self.minx), + self.calc_grid_position(current_A.y, self.miny), "xc") + plt.plot(self.calc_grid_position(current_B.x, self.minx), + self.calc_grid_position(current_B.y, self.miny), "xc") + # for stopping simulation with the esc key. + plt.gcf().canvas.mpl_connect('key_release_event', + lambda event: + [exit(0) if + event.key == 'escape' else None]) + if len(closed_set_A.keys()) % 10 == 0: + plt.pause(0.001) + + if c_id_A in closed_set_B: + print("Find goal") + meetpointA = closed_set_A[c_id_A] + meetpointB = closed_set_B[c_id_A] + break + + elif c_id_B in closed_set_A: + print("Find goal") + meetpointA = closed_set_A[c_id_B] + meetpointB = closed_set_B[c_id_B] + break + + # expand_grid search grid based on motion model + for i, _ in enumerate(self.motion): + breakA = False + breakB = False + + node_A = self.Node(current_A.x + self.motion[i][0], + current_A.y + self.motion[i][1], + current_A.cost + self.motion[i][2], + c_id_A, None) + node_B = self.Node(current_B.x + self.motion[i][0], + current_B.y + self.motion[i][1], + current_B.cost + self.motion[i][2], + c_id_B, None) + + n_id_A = self.calc_grid_index(node_A) + n_id_B = self.calc_grid_index(node_B) + + # If the node is not safe, do nothing + if not self.verify_node(node_A): + breakA = True + + if not self.verify_node(node_B): + breakB = True + + if (n_id_A not in closed_set_A) and (n_id_A not in + open_set_A) and (not + breakA): + node_A.parent = current_A + open_set_A[n_id_A] = node_A + + if (n_id_B not in closed_set_B) and (n_id_B not in + open_set_B) and (not + breakB): + node_B.parent = current_B + open_set_B[n_id_B] = node_B + + rx, ry = self.calc_final_path_bidir( + meetpointA, meetpointB, closed_set_A, closed_set_B) + return rx, ry + + # takes both set and meeting nodes and calculate optimal path + def calc_final_path_bidir(self, n1, n2, setA, setB): + rxA, ryA = self.calc_final_path(n1, setA) + rxB, ryB = self.calc_final_path(n2, setB) + + rxA.reverse() + ryA.reverse() + + rx = rxA + rxB + ry = ryA + ryB + + return rx, ry + + def calc_final_path(self, ngoal, closedset): + # generate final course + rx, ry = [self.calc_grid_position(ngoal.x, self.minx)], [ + self.calc_grid_position(ngoal.y, self.miny)] + n = closedset[ngoal.pind] + while n is not None: + rx.append(self.calc_grid_position(n.x, self.minx)) + ry.append(self.calc_grid_position(n.y, self.miny)) + n = n.parent + + return rx, ry + + def calc_grid_position(self, index, minp): + """ + calc grid position + + :param index: + :param minp: + :return: + """ + pos = index * self.reso + minp + return pos + + def calc_xyindex(self, position, min_pos): + return round((position - min_pos) / self.reso) + + def calc_grid_index(self, node): + return (node.y - self.miny) * self.xwidth + (node.x - self.minx) + + def verify_node(self, node): + px = self.calc_grid_position(node.x, self.minx) + py = self.calc_grid_position(node.y, self.miny) + + if px < self.minx: + return False + elif py < self.miny: + return False + elif px >= self.maxx: + return False + elif py >= self.maxy: + return False + + # collision check + if self.obmap[node.x][node.y]: + return False + + return True + + def calc_obstacle_map(self, ox, oy): + + self.minx = round(min(ox)) + self.miny = round(min(oy)) + self.maxx = round(max(ox)) + self.maxy = round(max(oy)) + print("minx:", self.minx) + print("miny:", self.miny) + print("maxx:", self.maxx) + print("maxy:", self.maxy) + + self.xwidth = round((self.maxx - self.minx) / self.reso) + self.ywidth = round((self.maxy - self.miny) / self.reso) + print("xwidth:", self.xwidth) + print("ywidth:", self.ywidth) + + # obstacle map generation + self.obmap = [[False for _ in range(self.ywidth)] + for _ in range(self.xwidth)] + for ix in range(self.xwidth): + x = self.calc_grid_position(ix, self.minx) + for iy in range(self.ywidth): + y = self.calc_grid_position(iy, self.miny) + for iox, ioy in zip(ox, oy): + d = math.hypot(iox - x, ioy - y) + if d <= self.rr: + self.obmap[ix][iy] = True + break + + @staticmethod + def get_motion_model(): + # dx, dy, cost + motion = [[1, 0, 1], + [0, 1, 1], + [-1, 0, 1], + [0, -1, 1], + [-1, -1, math.sqrt(2)], + [-1, 1, math.sqrt(2)], + [1, -1, math.sqrt(2)], + [1, 1, math.sqrt(2)]] + + return motion + + +def main(): + print(__file__ + " start!!") + + # start and goal position + sx = 10.0 # [m] + sy = 10.0 # [m] + gx = 50.0 # [m] + gy = 50.0 # [m] + grid_size = 2.0 # [m] + robot_radius = 1.0 # [m] + + # set obstacle positions + ox, oy = [], [] + for i in range(-10, 60): + ox.append(i) + oy.append(-10.0) + for i in range(-10, 60): + ox.append(60.0) + oy.append(i) + for i in range(-10, 61): + ox.append(i) + oy.append(60.0) + for i in range(-10, 61): + ox.append(-10.0) + oy.append(i) + for i in range(-10, 40): + ox.append(20.0) + oy.append(i) + for i in range(0, 40): + ox.append(40.0) + oy.append(60.0 - i) + + if show_animation: # pragma: no cover + plt.plot(ox, oy, ".k") + plt.plot(sx, sy, "og") + plt.plot(gx, gy, "ob") + plt.grid(True) + plt.axis("equal") + + bi_bfs = BidirectionalBreadthFirstSearchPlanner( + ox, oy, grid_size, robot_radius) + rx, ry = bi_bfs.planning(sx, sy, gx, gy) + + if show_animation: # pragma: no cover + plt.plot(rx, ry, "-r") + plt.pause(0.01) + plt.show() + + +if __name__ == '__main__': + main()