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$ git clone git@github.com:duckietown/challenge-aido_LF-template-random.git

$ cd challenge-aido_LF-template-random

$ dts challenges submit --challenge CHALLENGE_NAME

$ dts challenges evaluate --challenge CHALLENGE_NAME

$ dts challenges follow --submission SUBMISSION_NUMBER

submission.yaml
Dockerfile
Makefile
requirements.txt
solution.py

challenge: [c1,c2]
protocol: aido2_db18_agent-z2
user-label: random_agent
user-payload: 

def on_received_observations(self, context: Context, data: DB20ObservationsWithTimestamp):
        profiler = context.get_profiler()
        camera: JPGImageWithTimestamp = data.camera
        odometry: DB20OdometryWithTimestamp = data.odometry
        context.info(f"camera timestamp: {camera.timestamp}")
        context.info(f"odometry timestamp: {odometry.timestamp}")
        with profiler.prof("jpg2rgb"):
            _rgb = jpg2rgb(camera.jpg_data)

def on_received_get_commands(self, context: Context, data: GetCommands):
        self.n += 1

        # behavior = 0 # random trajectory
        behavior = 1  # primary motions

        if behavior == 0:
            pwm_left = np.random.uniform(0.5, 1.0)
            pwm_right = np.random.uniform(0.5, 1.0)
            col = RGB(0.0, 1.0, 1.0)
        elif behavior == 1:
            t = data.at_time
            d = 1.0

            phases = [
                (+1, -1, RGB(1.0, 0.0, 0.0)),
                (-1, +1, RGB(0.0, 1.0, 0.0)),
                (+1, +1, RGB(0.0, 0.0, 1.0)),
                (-1, -1, RGB(1.0, 1.0, 0.0)),
            ]
            phase = int(t / d) % len(phases)
            pwm_right, pwm_left, col = phases[phase]

        else:
            raise ValueError(behavior)

        led_commands = LEDSCommands(col, col, col, col, col)
        pwm_commands = PWMCommands(motor_left=pwm_left, motor_right=pwm_right)
        commands = DB20Commands(pwm_commands, led_commands)
        context.write("commands", commands)