businessbot.py

import pimoroni_i2c
import breakout_vl53l5cx
import time
from ulab import numpy
from motor import Motor, pico_motor_shim
from pimoroni import NORMAL_DIR, REVERSED_DIR

# The VL53L5CX requires a firmware blob to start up.
# Make sure you upload "vl53l5cx_firmware.bin" via Thonny to the root of your filesystem
# You can find it here: https://github.com/ST-mirror/VL53L5CX_ULD_driver/blob/no-fw/lite/en/vl53l5cx_firmware.bin

# This example attempts to track a "bright" object (such as a white business card).
# It uses reflectance to identify the target and compute the X/Y coordinates
# of its "center of mass" in the sensors view.
# We then use the object tracking to drive a little robot towards a business card onna stick!

# Motion indication only works at distances > 400mm so it's not
# really useful as a method to reject data.

# Configure your distance and brightness thresholds to suit your object
DISTANCE_THRESHOLD = 400  # Distance in mm
REFLECTANCE_THRESHOLD = 60  # Estimated reflectance in %

PINS_BREAKOUT_GARDEN = {"sda": 4, "scl": 5}
PINS_PICO_EXPLORER = {"sda": 20, "scl": 21}

# Sensor startup time is proportional to i2c baudrate
# HOWEVER many sensors may not run at > 400KHz (400000)
i2c = pimoroni_i2c.PimoroniI2C(**PINS_BREAKOUT_GARDEN, baudrate=2_000_000)

# Speed / distance constants for the robot - modify these to change driving behaviour!
DRIVING_SPEED = 0.7    # The speed to drive the wheels at when going forward
TURNING_SPEED = 0.2    # The speed to drive the wheels at when turning
GOAL_DISTANCE = 100.0  # The distance in mm the robot will keep an object in front of it
SPEED_RANGE = 50.0     # The distance an object is from the goal that will have the robot drive at full speed

# Setup the left and right motors - we're connecting our motors via a Motor SHIM for Pico.
# Swap the directions if this is different to your setup
left = Motor(pico_motor_shim.MOTOR_1, direction=REVERSED_DIR)
right = Motor(pico_motor_shim.MOTOR_2, direction=NORMAL_DIR)

# Setup the VL53L5CX sensor
print("Starting up sensor...")
t_sta = time.ticks_ms()
sensor = breakout_vl53l5cx.VL53L5CX(i2c)
t_end = time.ticks_ms()
print("Done in {}ms...".format(t_end - t_sta))

# Make sure to set resolution and other settings *before* you start ranging
sensor.set_resolution(breakout_vl53l5cx.RESOLUTION_8X8)
sensor.set_ranging_frequency_hz(15)
sensor.start_ranging()

while True:
    time.sleep(1.0 / 60)
    if sensor.data_ready():
        # "data" is a namedtuple (attrtuple technically)
        # it includes average readings as "distance_avg" and "reflectance_avg"
        # plus a full 4x4 or 8x8 set of readings (as a 1d tuple) for both values.
        data = sensor.get_data()

        reflectance = numpy.array(data.reflectance).reshape((8, 8))
        distance = numpy.array(data.distance).reshape((8, 8))

        scalar = 0
        target_distance = 0
        n_distances = 0
        # Filter out unwanted reflectance values
        for ox in range(8):
            for oy in range(8):
                d = distance[ox][oy]
                r = reflectance[ox][oy]
                if d > DISTANCE_THRESHOLD or r < REFLECTANCE_THRESHOLD:
                    reflectance[ox][oy] = 0
                else:
                    scalar += r

        # Get a total from all the distances within our accepted target
        for ox in range(8):
            for oy in range(8):
                d = distance[ox][oy]
                r = reflectance[ox][oy]
                if r > 0:
                    target_distance += d
                    n_distances += 1

        # Average the target distance
        if n_distances > 0:
            target_distance /= n_distances
        else:
            target_distance = 0

        # Flip reflectance now we've applied distance
        # both fields are upside-down!
        reflectance = numpy.flip(reflectance, axis=0)

        # Calculate the center of mass along X and Y
        x = 0
        y = 0
        if scalar > 0:
            for ox in range(8):
                for oy in range(8):
                    y += reflectance[ox][oy] * ox
            y /= scalar
            y /= 3.5
            y -= 1.0

            for oy in range(8):
                for ox in range(8):
                    x += reflectance[ox][oy] * oy
            x /= scalar
            x /= 3.5
            x -= 1.0

            print("Object detected at x: {:.2f}, y: {:.2f}".format(x, y))

            # Our robot will try and keep the object a goal distance in front of it.
            # If the object gets closer it will reverse, if the object gets further away it will drive forward.
            scale = (target_distance - GOAL_DISTANCE) / SPEED_RANGE
            spd = max(min(scale, 1.0), -1.0) * DRIVING_SPEED

            print("Distance is {:.1f} mm. Speed is {:.2f}".format(target_distance, spd))

            left.speed(spd - (x * TURNING_SPEED))
            right.speed(spd + (x * TURNING_SPEED))
        else:
            left.coast()
            right.coast()