def measure():
global blind_steps
blind_steps = 0
measurement = make_measurement(bot, grid, variance=1)
particle_filter.measure(measurement, measurement_likelihood)
ui.draw_bots(canvas, bot, particle_filter.particles)
ui.draw_measurement(canvas, bot, measurement)
def move():
ui.clear_measurement(canvas)
global bot, blind_steps, should_filter_reset
blind_steps += 1
direction = vote()
bot = movement_model(bot, direction, .1, 0)
particle_filter.move(direction, movement_model)
ui.draw_bots(canvas, bot, particle_filter.particles)
measurement = make_measurement(bot, grid, variance=1)
if min(measurement) <= SAFETY_BUFFER:
instructions_text.set("I'm awfully close to a wall. Lemme reset the filter.")
should_filter_reset = True
def on_click(event):
location = int(event.y / 3), int(event.x / 3)
global bot, setting_goal, plan, setting_bot, goal
if setting_goal:
goal = location
setting_goal = False
setting_bot = True
ui.draw_goal(canvas, goal)
instructions_text.set("Click to set bot location (hold while nav is computed)")
elif setting_bot:
bot = location
setting_bot = False
plan = nav.process_grid(goal, grid.occupancy, grid.danger, danger_weight=100)
# grid.preprocess()
instructions_text.set("Click the step button or press S to get started!")
reset_filter(None)
def reset_filter(event):
global particle_filter
particle_filter = pf.ParticleFilter(prior_distribution, particle_count=1000)
ui.draw_bots(canvas, bot, particle_filter.particles)
def reset_goal(event):
ui.clear_all(canvas)
global setting_goal, done
done = False
setting_goal = True
instructions_text.set("Click to set the goal location")