broken_robot.goto(target_bot.x*size_multiplier, target_bot.y*size_multiplier-200)
        broken_robot.stamp()
        prediction.setheading(target_bot.heading*180/pi)
        prediction.goto(position_guess[0]*size_multiplier, position_guess[1]*size_multiplier-200)
        prediction.stamp()
        #End of Visualization
    return localized

# This is a demo for what a strategy could look like. This one isn't very good.
def naive_next_pos(measurement, OTHER = None):
    """This strategy records the first reported position of the target and
    assumes that eventually the target bot will eventually return to that 
    position, so it always guesses that the first position will be the next."""
    if not OTHER: # this is the first measurement
        OTHER = measurement
    xy_estimate = OTHER 
    return xy_estimate, OTHER

# This is how we create a target bot. Check the robot.py file to understand
# How the robot class behaves.
test_target = robot(2.1, 4.3, 0.5, 2*pi / 34.0, 1.5)
measurement_noise = 0.05 * test_target.distance
test_target.set_noise(0.0, 0.0, measurement_noise)

demo_grading(estimate_next_pos, test_target)





Exemple #2
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        #Visualize it
        measuredbroken_robot.setheading(target_bot.heading * 180 / pi)
        measuredbroken_robot.goto(
            target_measurement[0] * size_multiplier,
            target_measurement[1] * size_multiplier - 100)
        measuredbroken_robot.stamp()
        broken_robot.setheading(target_bot.heading * 180 / pi)
        broken_robot.goto(target_bot.x * size_multiplier,
                          target_bot.y * size_multiplier - 100)
        chaser_robot.setheading(hunter_bot.heading * 180 / pi)
        chaser_robot.goto(hunter_bot.x * size_multiplier,
                          hunter_bot.y * size_multiplier - 100)
        estimation_robot.goto(estimation[0] * size_multiplier,
                              estimation[1] * size_multiplier - 100)

        #End of visualization
        ctr += 1
        if ctr >= 1000:
            print "It took too many steps to catch the target."
    return caught


target = robot(0.0, 10.0, 0.0, 2 * pi / 30, 1.5)
# measurement_noise = 2.0*target.distance # VERY NOISY!!
measurement_noise = .05 * target.distance  # VERY NOISY!!
target.set_noise(0.0, 0.0, measurement_noise)

hunter = robot(-10.0, -10.0, 0.0)

print demo_grading2(hunter, target, next_move)
Exemple #3
0
        broken_robot.goto(target_bot.x*size_multiplier, target_bot.y*size_multiplier-200)
        broken_robot.stamp()
        prediction.setheading(target_bot.heading*180/pi)
        prediction.goto(position_guess[0]*size_multiplier, position_guess[1]*size_multiplier-200)
        prediction.stamp()
        #End of Visualization
    return localized

# This is a demo for what a strategy could look like. This one isn't very good.
def naive_next_pos(measurement, OTHER = None):
    """This strategy records the first reported position of the target and
    assumes that eventually the target bot will eventually return to that 
    position, so it always guesses that the first position will be the next."""
    if not OTHER: # this is the first measurement
        OTHER = measurement
    xy_estimate = OTHER 
    return xy_estimate, OTHER

# This is how we create a target bot. Check the robot.py file to understand
# How the robot class behaves.
test_target = robot(2.1, 4.3, 0.5, 2*pi / 34.0, 1.5)
measurement_noise = 0.05 * test_target.distance
test_target.set_noise(0.0, 0.0, measurement_noise)

demo_grading(estimate_next_pos, test_target)





        #Visualize it
        measuredbroken_robot.setheading(target_bot.heading*180/pi)
        measuredbroken_robot.goto(target_measurement[0]*size_multiplier, target_measurement[1]*size_multiplier-100)
        measuredbroken_robot.stamp()
        broken_robot.setheading(target_bot.heading*180/pi)
        broken_robot.goto(target_bot.x*size_multiplier, target_bot.y*size_multiplier-100)
        chaser_robot.setheading(hunter_bot.heading*180/pi)
        chaser_robot.goto(hunter_bot.x*size_multiplier, hunter_bot.y*size_multiplier-100)
        if estimation:
            estimation_robot.goto(estimation[0]*size_multiplier, estimation[1]*size_multiplier-100)

        #End of visualization
        ctr += 1
        if ctr >= 1000:
            print "It took too many steps to catch the target."
    return caught

target = robot(0.0, 10.0, 0.0, 2*pi / 30, 1.5)
# measurement_noise = 2.0*target.distance # VERY NOISY!!
measurement_noise = .5*target.distance # VERY NOISY!!
target.set_noise(0.0, 0.0, measurement_noise)

hunter = robot(-10.0, -10.0, 0.0)

print demo_grading2(hunter, target, next_move)