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Open-source simulator for autonomous driving research.
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Want to know how to measure distance of detected objects using camera and radar sensor in CARLA #5395

Closed sbv198 closed 2 years ago

sbv198 commented 2 years ago
sbv198 commented 2 years ago

I have used camera RGB and radar i am getting vector 3D of each pixels generated by RADAR and for that i have used the code provided in carla documentation. i want to measure distance from an object using the image captured by camera. how to do that

any help is appreciated

thanks Sagar Varvariya

PatrickFSLin commented 2 years ago

the same question here...

sbv198 commented 2 years ago

@PatrickFSLin I used following code to measure average distance of detected objects. the following code you will find it on carla documentation as well.

  1. https://carla.readthedocs.io/en/latest/tuto_G_retrieve_data/#set-advanced-sensors
  2. https://carla.readthedocs.io/en/latest/ref_sensors/#depth-camera

refer this documents as well

RADAR sensor

    rad_bp = world.get_blueprint_library().find('sensor.other.radar')
    rad_bp.set_attribute('horizontal_fov', str(35))
    rad_bp.set_attribute('vertical_fov', str(20))
    rad_bp.set_attribute('range', str(20))
    rad_location = carla.Location(x=2.0, z=1.0)
    rad_rotation = carla.Rotation(pitch=5)
    rad_transform = carla.Transform(rad_location, rad_rotation)
    rad_ego = world.spawn_actor(rad_bp, rad_transform, attach_to=ego_vehicle,
                                attachment_type=carla.AttachmentType.Rigid)
    actor_list.append(rad_ego)

    def rad_callback(radar_data):
        velocity_range = 7.5  # m/s
        current_rot = radar_data.transform.rotation
        for detect in radar_data:
            azi = math.degrees(detect.azimuth)
            alt = math.degrees(detect.altitude)
            # The 0.25 adjusts a bit the distance so the dots can
            # be properly seen
            fw_vec = carla.Vector3D(x=detect.depth - 0.25)
            carla.Transform(
                carla.Location(),
                carla.Rotation(
                    pitch=current_rot.pitch + alt,
                    yaw=current_rot.yaw + azi,
                    roll=current_rot.roll)).transform(fw_vec)

            def clamp(min_v, max_v, value):
                return max(min_v, min(value, max_v))

            norm_velocity = detect.velocity / velocity_range  # range [-1, 1]
            r = int(clamp(0.0, 1.0, 1.0 - norm_velocity) * 255.0)
            g = int(clamp(0.0, 1.0, 1.0 - abs(norm_velocity)) * 255.0)
            b = int(abs(clamp(- 1.0, 0.0, - 1.0 - norm_velocity)) * 255.0)
            world.debug.draw_point(
                radar_data.transform.location + fw_vec,
                size=0.075,
                life_time=0.1,
                persistent_lines=False,
                color=carla.Color(r, g, b))

Array tranfer of obtained data

            points = np.frombuffer(radar_data.raw_data, dtype=np.dtype('f4'))
            points = np.reshape(points, (len(radar_data), 4))

            print(points)

 # code convert array into list and measure distance
            L = []
            pointslist=points.tolist()
            for i in range(len(pointslist)):
                L.append(pointslist[i-1][-1])

            ave = sum(L)/len(L)
            print(ave)

    rad_ego.listen(lambda radar_data: rad_callback(radar_data))
    print(rad_ego.listen)

good luck

AmirMz1 commented 2 years ago

Hello, thank you for your answer I want to get the distance to each car. Can you please guide me how to do this, what the radar sensor detects and how to set it only for cars.

@PatrickFSLin I used following code to measure average distance of detected objects. the following code you will find it on carla documentation as well.

  1. https://carla.readthedocs.io/en/latest/tuto_G_retrieve_data/#set-advanced-sensors
  2. https://carla.readthedocs.io/en/latest/ref_sensors/#depth-camera

refer this documents as well

RADAR sensor

    rad_bp = world.get_blueprint_library().find('sensor.other.radar')
    rad_bp.set_attribute('horizontal_fov', str(35))
    rad_bp.set_attribute('vertical_fov', str(20))
    rad_bp.set_attribute('range', str(20))
    rad_location = carla.Location(x=2.0, z=1.0)
    rad_rotation = carla.Rotation(pitch=5)
    rad_transform = carla.Transform(rad_location, rad_rotation)
    rad_ego = world.spawn_actor(rad_bp, rad_transform, attach_to=ego_vehicle,
                                attachment_type=carla.AttachmentType.Rigid)
    actor_list.append(rad_ego)

    def rad_callback(radar_data):
        velocity_range = 7.5  # m/s
        current_rot = radar_data.transform.rotation
        for detect in radar_data:
            azi = math.degrees(detect.azimuth)
            alt = math.degrees(detect.altitude)
            # The 0.25 adjusts a bit the distance so the dots can
            # be properly seen
            fw_vec = carla.Vector3D(x=detect.depth - 0.25)
            carla.Transform(
                carla.Location(),
                carla.Rotation(
                    pitch=current_rot.pitch + alt,
                    yaw=current_rot.yaw + azi,
                    roll=current_rot.roll)).transform(fw_vec)

            def clamp(min_v, max_v, value):
                return max(min_v, min(value, max_v))

            norm_velocity = detect.velocity / velocity_range  # range [-1, 1]
            r = int(clamp(0.0, 1.0, 1.0 - norm_velocity) * 255.0)
            g = int(clamp(0.0, 1.0, 1.0 - abs(norm_velocity)) * 255.0)
            b = int(abs(clamp(- 1.0, 0.0, - 1.0 - norm_velocity)) * 255.0)
            world.debug.draw_point(
                radar_data.transform.location + fw_vec,
                size=0.075,
                life_time=0.1,
                persistent_lines=False,
                color=carla.Color(r, g, b))

Array tranfer of obtained data

            points = np.frombuffer(radar_data.raw_data, dtype=np.dtype('f4'))
            points = np.reshape(points, (len(radar_data), 4))

            print(points)

 # code convert array into list and measure distance
            L = []
            pointslist=points.tolist()
            for i in range(len(pointslist)):
                L.append(pointslist[i-1][-1])

            ave = sum(L)/len(L)
            print(ave)

    rad_ego.listen(lambda radar_data: rad_callback(radar_data))
    print(rad_ego.listen)

good luck

sbv198 commented 2 years ago

@AmirMz1 Radar will detect obstacles infront of it and this code shown will show the detected points with its velocity, azimuth, altitude and longitudinal distance from radar.

You will need to do trial and error for mostly to know which points to take into consideration.

I think it is not possible to get the distance particularly from cars only. but my knowledge is limited.

You can see the images below for radar detection and its values

Points in_vehicle direction radar data radar points Radar_Points values

SExpert12 commented 1 year ago

Hello, thank you for your answer I want to get the distance to each car. Can you please guide me how to do this, what the radar sensor detects and how to set it only for cars.

@PatrickFSLin I used following code to measure average distance of detected objects. the following code you will find it on carla documentation as well.

  1. https://carla.readthedocs.io/en/latest/tuto_G_retrieve_data/#set-advanced-sensors
  2. https://carla.readthedocs.io/en/latest/ref_sensors/#depth-camera

refer this documents as well

RADAR sensor

    rad_bp = world.get_blueprint_library().find('sensor.other.radar')
    rad_bp.set_attribute('horizontal_fov', str(35))
    rad_bp.set_attribute('vertical_fov', str(20))
    rad_bp.set_attribute('range', str(20))
    rad_location = carla.Location(x=2.0, z=1.0)
    rad_rotation = carla.Rotation(pitch=5)
    rad_transform = carla.Transform(rad_location, rad_rotation)
    rad_ego = world.spawn_actor(rad_bp, rad_transform, attach_to=ego_vehicle,
                                attachment_type=carla.AttachmentType.Rigid)
    actor_list.append(rad_ego)

    def rad_callback(radar_data):
        velocity_range = 7.5  # m/s
        current_rot = radar_data.transform.rotation
        for detect in radar_data:
            azi = math.degrees(detect.azimuth)
            alt = math.degrees(detect.altitude)
            # The 0.25 adjusts a bit the distance so the dots can
            # be properly seen
            fw_vec = carla.Vector3D(x=detect.depth - 0.25)
            carla.Transform(
                carla.Location(),
                carla.Rotation(
                    pitch=current_rot.pitch + alt,
                    yaw=current_rot.yaw + azi,
                    roll=current_rot.roll)).transform(fw_vec)

            def clamp(min_v, max_v, value):
                return max(min_v, min(value, max_v))

            norm_velocity = detect.velocity / velocity_range  # range [-1, 1]
            r = int(clamp(0.0, 1.0, 1.0 - norm_velocity) * 255.0)
            g = int(clamp(0.0, 1.0, 1.0 - abs(norm_velocity)) * 255.0)
            b = int(abs(clamp(- 1.0, 0.0, - 1.0 - norm_velocity)) * 255.0)
            world.debug.draw_point(
                radar_data.transform.location + fw_vec,
                size=0.075,
                life_time=0.1,
                persistent_lines=False,
                color=carla.Color(r, g, b))

Array tranfer of obtained data

            points = np.frombuffer(radar_data.raw_data, dtype=np.dtype('f4'))
            points = np.reshape(points, (len(radar_data), 4))

            print(points)

 # code convert array into list and measure distance
            L = []
            pointslist=points.tolist()
            for i in range(len(pointslist)):
                L.append(pointslist[i-1][-1])

            ave = sum(L)/len(L)
            print(ave)

    rad_ego.listen(lambda radar_data: rad_callback(radar_data))
    print(rad_ego.listen)

good luck

have you done this part where you can get the distance of each car?