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graph_motion_planning.py
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graph_motion_planning.py
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import argparse
import time
import msgpack
from enum import Enum, auto
import numpy as np
from graph_planning_utils import Sampler, a_star, heuristic, create_grid, create_graph, load_csv
from udacidrone import Drone
from udacidrone.connection import MavlinkConnection
from udacidrone.messaging import MsgID
from udacidrone.frame_utils import global_to_local
class States(Enum):
MANUAL = auto()
ARMING = auto()
TAKEOFF = auto()
WAYPOINT = auto()
LANDING = auto()
DISARMING = auto()
PLANNING = auto()
class MotionPlanning(Drone):
def __init__(self, connection, global_goal_position=np.array([-122.3990892, 37.79342573, -5.0], dtype='Float64')):
super().__init__(connection)
self.target_position = np.array([0.0, 0.0, 0.0])
self.waypoints = []
self.in_mission = True
self.check_state = {}
self.global_goal_position = global_goal_position
# initial state
self.flight_state = States.MANUAL
# register all your callbacks here
self.register_callback(MsgID.LOCAL_POSITION, self.local_position_callback)
self.register_callback(MsgID.LOCAL_VELOCITY, self.velocity_callback)
self.register_callback(MsgID.STATE, self.state_callback)
self.N_SAMPLE = 50
self.K = 8
def local_position_callback(self):
if self.flight_state == States.TAKEOFF:
if -1.0 * self.local_position[2] > 0.95 * self.target_position[2]:
self.waypoint_transition()
elif self.flight_state == States.WAYPOINT:
if np.linalg.norm(self.target_position[0:2] - self.local_position[0:2]) < 1.0:
if len(self.waypoints) > 0:
self.waypoint_transition()
else:
if np.linalg.norm(self.local_velocity[0:2]) < 1.0:
self.landing_transition()
def velocity_callback(self):
if self.flight_state == States.LANDING:
if self.global_position[2] - self.global_home[2] < 0.1:
if abs(self.local_position[2]) < 0.01:
self.disarming_transition()
def state_callback(self):
if self.in_mission:
if self.flight_state == States.MANUAL:
self.arming_transition()
elif self.flight_state == States.ARMING:
if self.armed:
self.plan_path()
elif self.flight_state == States.PLANNING:
self.takeoff_transition()
elif self.flight_state == States.DISARMING:
if ~self.armed & ~self.guided:
self.manual_transition()
def arming_transition(self):
self.flight_state = States.ARMING
print("arming transition")
self.arm()
self.take_control()
def takeoff_transition(self):
self.flight_state = States.TAKEOFF
print("takeoff transition")
self.takeoff(self.target_position[2])
def waypoint_transition(self):
self.flight_state = States.WAYPOINT
print("waypoint transition")
self.target_position = self.waypoints.pop(0)
print('target position', self.target_position)
self.cmd_position(self.target_position[0], self.target_position[1], self.target_position[2], self.target_position[3])
def landing_transition(self):
self.flight_state = States.LANDING
print("landing transition")
self.land()
def disarming_transition(self):
self.flight_state = States.DISARMING
print("disarm transition")
self.disarm()
self.release_control()
def manual_transition(self):
self.flight_state = States.MANUAL
print("manual transition")
self.stop()
self.in_mission = False
def send_waypoints(self):
print("Sending waypoints to simulator ...")
data = msgpack.dumps(self.waypoints)
self.connection._master.write(data)
def plan_path(self):
self.flight_state = States.PLANNING
print("Searching for a path ...")
TARGET_ALTITUDE = 5
SAFETY_DISTANCE = 5
self.target_position[2] = TARGET_ALTITUDE
# TODO: read lat0, lon0 from colliders into floating point values
filename = 'colliders.csv'
lat0, lon0 = load_csv(filename)
# TODO: set home position to (lon0, lat0, 0)
self.set_home_position(lon0, lat0, 0)
# TODO: retrieve current global position
# TODO: convert to current local position using global_to_local()
local_position = global_to_local(self.global_position, self.global_home)
print('global home {0}, position {1}, local position {2}'.format(self.global_home, self.global_position,
self.local_position))
# Read in obstacle map
data = np.loadtxt(filename, delimiter=',', dtype='Float64', skiprows=2)
# Define a grid for a particular altitude and safety margin around obstacles
grid, north_offset, east_offset = create_grid(data, TARGET_ALTITUDE, SAFETY_DISTANCE)
print("North offset = {0}, east offset = {1}".format(north_offset, east_offset))
# Define starting point on the grid (this is just grid center)
# grid_start = (int(np.ceil(local_position[0] - north_offset)), int(np.ceil(local_position[1] - east_offset))) # TODO: convert start position to current position rather than map center
start = (int(np.ceil(local_position[0])), int(np.ceil(local_position[1])), int(np.ceil(local_position[2]))) # TODO: convert start position to current position rather than map center
# Set goal as some arbitrary position on the grid
local_goal_position = global_to_local(self.global_goal_position, self.global_home)
#grid_goal = (int(np.ceil(local_goal_position[0] - north_offset)), int(np.ceil(local_goal_position[1] - east_offset))) # TODO: adapt to set goal as latitude / longitude position and convert
goal = (int(np.ceil(local_goal_position[0])), int(np.ceil(local_goal_position[1])), int(np.ceil(local_goal_position[2]))) # TODO: adapt to set goal as latitude / longitude position and convert
print('Local Start and Goal: ', start, goal)
#print('Local Start and Goal: ', grid_start, grid_goal)
## Sampling points from the data
sampler = Sampler(data, start, goal)
polygons = sampler._polygons
nodes = sampler.circular_random(self.N_SAMPLE)
print("Valid sample nodes: %i" %len(nodes))
## Create graph based on samples
g = create_graph(nodes, self.K, polygons)
print("Number of edges", len(g.edges))
# Run A* to find a path from start to goal
# move to a different search space such as a graph (not done here)
path, _ = a_star(g, heuristic, start, goal)
# Convert path to waypoints
# waypoints = [[p[0] + north_offset, p[1] + east_offset, TARGET_ALTITUDE, 0] for p in path]
waypoints = [[p[0], p[1], p[2], 0] for p in path]
print(waypoints)
# Set self.waypoints
self.waypoints = waypoints
# TODO: send waypoints to sim
self.send_waypoints()
def start(self):
self.start_log("Logs", "NavLog.txt")
print("starting connection")
self.connection.start()
# Only required if they do threaded
# while self.in_mission:
# pass
self.stop_log()
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--port', type=int, default=5760, help='Port number')
parser.add_argument('--host', type=str, default='127.0.0.1', help="host address, i.e. '127.0.0.1'")
parser.add_argument('--goal_lon', type=str, default=' -122.3990892', help="Goal longitude")
parser.add_argument('--goal_lat', type=str, default='37.79342573', help="Goal latitude")
parser.add_argument('--goal_alt', type=str, default='-5.0', help="Goal altitude")
args = parser.parse_args()
conn = MavlinkConnection('tcp:{0}:{1}'.format(args.host, args.port), timeout=60)
goal_global_position = np.fromstring(f'{args.goal_lon},{args.goal_lat},{args.goal_alt}', dtype='Float64', sep=',')
drone = MotionPlanning(conn)
time.sleep(1)
drone.start()