PX4-Autopilot/docs/ko/computer_vision/visual_inertial_odometry.md

# Visual Inertial Odometry (VIO)

_Visual Inertial Odometry_ (VIO) is a [computer vision](../computer_vision/index.md) technique used for estimating the 3D _pose_ (local position and orientation) and _velocity_ of a moving vehicle relative to a _local_ starting position.
GPS가 없거나 신뢰할 수없는 상황 (예 : 실내 또는 다리 아래에서 비행시)에서 기체 내비게이션용으로 사용됩니다.

VIO uses [Visual Odometry](https://en.wikipedia.org/wiki/Visual_odometry) to estimate vehicle _pose_ from camera images, combined with inertial measurements from the vehicle IMU (to correct for errors associated with rapid vehicle movement resulting in poor image capture).

This topic gives guidance on configuring PX4 and a companion computer for a VIO setup.

:::info
The suggested setup uses ROS for routing VIO information to PX4.
However, PX4 itself does not care about the source of messages, provided they are provided via the appropriate [MAVLink Interface](../ros/external_position_estimation.md#px4-mavlink-integration).
:::

## Suggested Setup

A hardware and software setup for VIO is suggested in the sections below as an illustration of how to interface a VIO system with PX4. It makes use of an off-the-shelf tracking camera and a companion computer running ROS.
ROS is used to read odometry information from the camera and supply it to PX4.

An example of a suitable tracking camera is the [Intel® RealSense™ Tracking Camera T265](../peripherals/camera_t265_vio.md).

### 카메라 장착

카메라를 보조 컴퓨터에 연결하고 프레임에 장착합니다.

- 가능하면 렌즈가 아래쪽을 향하도록 카메라를 장착하십시오 (기본값).
- Cameras are typically very sensitive to vibration; a soft mounting is recommended (e.g. using vibration isolation foam).

### Companion Setup

To setup ROS and PX4:

- On the companion computer, install and configure [MAVROS](../ros/mavros_installation.md).

- Implement and run a ROS node to read data from the camera and publish the VIO odometry using MAVROS.
  - See the [VIO ROS node](#vio_ros_node) section below for details of the requirements for this node.

- Follow the instructions [below](#ekf2_tuning) for tuning the PX4 EKF2 estimator.

- 비행 컨트롤러 연결을 확인하십시오.

  :::tip
  You can use the _QGroundControl_ [MAVLink Inspector](https://docs.qgroundcontrol.com/master/en/qgc-user-guide/analyze_view/mavlink_inspector.html) to verify that you're getting `ODOMETRY` or `VISION_POSITION_ESTIMATE` messages (or check for `HEARTBEAT` messages that have the component id 197 (`MAV_COMP_ID_VISUAL_INERTIAL_ODOMETRY`)).

:::

- [Verify that VIO is set up correctly](#verify_estimate) before your first flight!

### ROS VIO node {#vio_ros_node}

In this suggested setup, a ROS node is required to

1. interface with the chosen camera or sensor hardware,
2. produce odometry messages containing the position estimate, which will be sent to PX4 using MAVROS, and
3. publish messages to indicate the VIO system status.

The implementation of the ROS node will be specific to the camera used and will need to be developed to use the interface and drivers appropriate for the camera.

The odometry messages should be of the type [`nav_msgs/Odometry`](https://docs.ros.org/en/noetic/api/nav_msgs/html/msg/Odometry.html) and published to the topic `/mavros/odometry/out`.

System status messages of the type [`mavros_msgs/CompanionProcessStatus`](https://github.com/mavlink/mavros/blob/master/mavros_msgs/msg/CompanionProcessStatus.msg) should be published to the topic `/mavros/companion_process/status`.
These should identify the component as `MAV_COMP_ID_VISUAL_INERTIAL_ODOMETRY` (197) and indicate the `state` of the system. Recommended status values are:

- `MAV_STATE_ACTIVE` when the VIO system is functioning as expected,
- `MAV_STATE_CRITICAL` when the VIO system is functioning, but with low confidence, and
- `MAV_STATE_FLIGHT_TERMINATION` when the system has failed or the estimate confidence is unacceptably low.

### PX4 Tuning {#ekf2_tuning}

EKF2에서 외부 위치 정보를 사용하려면 다음 매개 변수를 설정하여야 합니다.

| 매개변수                                                                                                                                                                                                                                                                                                                                                                                                                      | 외부 위치 추정 설정                                                                                                                                             |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------- |
| [EKF2_EV_CTRL](../advanced_config/parameter_reference.md#EKF2_EV_CTRL)                                                                                                                                                                                                                                                                                                          | Set _horizontal position fusion_, _vertical vision fusion_, _velocity fusion_, and _yaw fusion_ according to your desired fusion model. |
| [EKF2_HGT_REF](../advanced_config/parameter_reference.md#EKF2_HGT_REF)                                                                                                                                                                                                                                                                                                          | Set to _Vision_ to use the vision as the reference sensor for altitude estimation.                                                      |
| [EKF2_EV_DELAY](../advanced_config/parameter_reference.md#EKF2_EV_DELAY)                                                                                                                                                                                                                                                                                                        | 측정 타임스탬프와 "실제" 캡처 시간 간의 차이로 설정합니다. For more information see [below](#tuning-EKF2_EV_DELAY).                             |
| [EKF2_EV_POS_X](../advanced_config/parameter_reference.md#EKF2_EV_POS_X), [EKF2_EV_POS_Y](../advanced_config/parameter_reference.md#EKF2_EV_POS_Y), [EKF2_EV_POS_Z](../advanced_config/parameter_reference.md#EKF2_EV_POS_Z) | Set the position of the vision sensor with respect to the vehicle's body frame.                                                         |

These can be set in _QGroundControl_ > **Vehicle Setup > Parameters > EKF2** (remember to reboot the flight controller in order for parameter changes to take effect).

For more detailed/additional information, see: [Using PX4's Navigation Filter (EKF2) > External Vision System](../advanced_config/tuning_the_ecl_ekf.md#external-vision-system).

#### Tuning EKF2_EV_DELAY {#tuning-EKF2_EV_DELAY}

[EKF2_EV_DELAY](../advanced_config/parameter_reference.md#EKF2_EV_DELAY) is the _Vision Position Estimator delay relative to IMU measurements_.
즉, 비전 시스템 타임스탬프와 IMU 클록 (EKF2의 "기본 클록")에 의해 기록된 "실제" 캡처 시간 간의 차이입니다.

Technically this can be set to 0 if there is correct timestamping (not just arrival time) and timesync (e.g. NTP) between MoCap and (for example) ROS computers.
In reality, this may need some empirical tuning because delays in the communication chain are very setup-specific.
It is rare that a system is set up with an entirely synchronised chain!

IMU 속도와 EV 속도 사이의 오프셋을 확인하여 로그에서 대략적인 지연 추정치를 얻을 수 있습니다.

![ekf2_ev_delay log](../../assets/ekf2/ekf2_ev_delay_tuning.png)

:::info
A plot of external data vs. onboard estimate (as above) can be generated using [FlightPlot](../log/flight_log_analysis.md#flightplot) or similar flight analysis tools.
:::

이 값은 동적 기동 중에 가장 낮은 EKF 혁신을 산출하는 값을 찾기 위하여, 매개변수를 변경하여 추가 튜닝할 수 있습니다.

## Check/Verify VIO Estimate {#verify_estimate}

:::info
The [MAV_ODOM_LP](../advanced_config/parameter_reference.md#MAV_ODOM_LP) parameter mentioned below was removed in PX4 v1.14.
This section needs to be updated. <!-- https://github.com/PX4/PX4-Autopilot/pull/20501#issuecomment-1993788815 -->
:::

Perform the following checks to verify that VIO is working properly _before_ your first flight:

- Set the PX4 parameter `MAV_ODOM_LP` to `1`.
  PX4 will then stream back the received external pose as MAVLink [ODOMETRY](https://mavlink.io/en/messages/common.html#ODOMETRY) messages.
  You can check these MAVLink messages with the _QGroundControl_ [MAVLink Inspector](https://docs.qgroundcontrol.com/master/en/qgc-user-guide/analyze_view/mavlink_inspector.html)
- Yaw the vehicle until the quaternion of the `ODOMETRY` message is very close to a unit quaternion (w=1, x=y=z=0).
  - At this point, the body frame is aligned with the reference frame of the external pose system.
  - 기체를 구르거나 피칭하지 않고 단위 쿼터니언에 가까운 쿼터니언을 얻을 수 없다면, 여전히 프레임에 피치 또는 롤 오프셋이 있을 수 있습니다.
    이 경우에는 더 이상 진행하지 말고, 좌표 프레임을 다시 확인하십시오.
- Once aligned, you can pick the vehicle up from the ground and you should see the position's z coordinate decrease.
  Moving the vehicle in the forward direction should increase the position's x coordinate.
  Moving the vehicle to the right should increase the y coordinate.
- Check that linear velocities in the message are expressed in the _FRD_ body frame reference frame.
- Set the PX4 parameter `MAV_ODOM_LP` back to 0.
  PX4 will stop streaming the `ODOMETRY` message back.

이러한 단계가 유지되면, 첫 번째 비행을 시도할 수 있습니다.

1. Put the vehicle on the ground and start streaming `ODOMETRY` feedback (as above).
   스로틀 스틱을 내리고 모터를 작동시키십시오.

   이때 왼쪽 스틱을 가장 낮은 위치에 놓고, 위치 제어로 전환합니다.
   초록불이 켜져야 합니다.
   녹색 표시등은 위치 피드백을 사용할 수 있고, 위치 제어가 활성화되었음을 알려줍니다.

2. 기체가 고도를 유지하도록 스로틀 스틱을 중간(데드 존)에 놓습니다.
   스틱을 올리면 기준 고도가 증가하고 값을 낮추면 감소합니다.
   Similarly, the other stick will change the position over the ground.

3. Increase the value of the throttle stick and the vehicle will take off. Move it back to the middle immediately afterwards.

4. 기체가 제자리를 유지하는 지 확인하십시오.

## 문제 해결

First, make sure MAVROS is able to connect successfully to the flight controller.

제대로 연결되는 경우 일반적인 문제 해결 방법은 다음과 같습니다.

- **Problem:** I get drift / flyaways when the drone flies, but not when I carry it around with the props off.
  - If using the [T265](../peripherals/camera_t265_vio.md) try soft-mounting it (this camera is very sensitive to high-frequency vibrations).

- **Problem:** I get toilet-bowling when VIO is enabled.
  - 카메라의 방향이 시작 파일의 변환과 일치하는 지 확인합니다.
    Use the _QGroundControl_ [MAVLink Inspector](https://docs.qgroundcontrol.com/master/en/qgc-user-guide/analyze_view/mavlink_inspector.html) to verify that the velocities in the `ODOMETRY` message coming from MAVROS are aligned to the FRD coordinate system.

- **Problem:** I want to use vision position to do loop closing, and also want to run GPS.
  - 이문제는 EKF를 혼란스럽게 할 것이기 때문에 정말 어렵습니다.
    테스트에서 비전 속도를 사용하는 것이 더 안정적입니다 (이 설정을 신뢰할 수있는 방법을 찾으면 알려주십시오).

## 개발자 정보

Developers who are interested in extending this implementation (or writing a different one, which might not depend on ROS) should see [Using Vision or Motion Capture Systems for Position Estimation](../ros/external_position_estimation.md).

이 항목에서는 LPE Estimator (사용되지 않음)와 함께 사용할 VIO를 구성하는 방법도 설명합니다.

## 추가 정보

- [Using PX4's Navigation Filter (EKF2) > External Vision System](../advanced_config/tuning_the_ecl_ekf.md#external-vision-system)