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feat(tracking_object_merger): merge tracked object. especially for fa…
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…r radar object and conventional lidar object (autowarefoundation#4340)

* init package: migrate from object merger

Signed-off-by: yoshiri <[email protected]>

* add node outline and check build passed

Signed-off-by: yoshiri <[email protected]>

* add util functions to interpolate tracked objs

Signed-off-by: yoshiri <[email protected]>

* add object merger function using interpolation

Signed-off-by: yoshiri <[email protected]>

* create object merger utils

Signed-off-by: yoshiri <[email protected]>

* add kinematics velocity merger

Signed-off-by: yoshiri <[email protected]>

* add association and merger

Signed-off-by: yoshiri <[email protected]>

* rename perception_utils to object_recognition_utils

Signed-off-by: yoshiri <[email protected]>

* add comment and complete main subscriber

Signed-off-by: yoshiri <[email protected]>

* add parameter control and rename some executable files

Signed-off-by: yoshiri <[email protected]>

* refactoring: fix apparent bugs

Signed-off-by: yoshiri <[email protected]>

* add debug tools to check association

Signed-off-by: yoshiri <[email protected]>

* temporary fix: radar tracker node name to anon

Signed-off-by: yoshiri <[email protected]>

* debug: data association tuning

Signed-off-by: yoshiri <[email protected]>

* rename copyright and add merger util function

Signed-off-by: yoshiri <[email protected]>

* add tracker_state and update association

Signed-off-by: yoshiri <[email protected]>

* update decorative tracker by using tracker_state

Signed-off-by: yoshiri <[email protected]>

* update system around measurement state function

Signed-off-by: yoshiri <[email protected]>

* fix radar object not merged problem

Signed-off-by: yoshiri <[email protected]>

* add existence probability control

Signed-off-by: yoshiri <[email protected]>

* create const function

Signed-off-by: yoshiri <[email protected]>

* change association settings depend on measurement and tracker state

Signed-off-by: yoshiri <[email protected]>

* fix association matrix

Signed-off-by: yoshiri <[email protected]>

* put hardcoded node parameter to yaml file

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* move tracker state parameter to yaml file

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* remove prediction failed objects

Signed-off-by: yoshiri <[email protected]>

* fix bug when none closest time sub objects found

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* add velocity diff gate in association

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* fix object interpolation problem

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* use fixed object interpolation

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* add README

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* add interpolated sub object publisher for debug

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* add debug message and fix interpolation

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* update README

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* fix unintended changes in radar tracking launch

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* add CmakeLists version

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* remove unnecessary debug description and type cast causes build warning

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* fix spell-check error

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* replace autoware_utils.hpp

Signed-off-by: yoshiri <[email protected]>

---------

Signed-off-by: yoshiri <[email protected]>
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YoshiRi committed Oct 16, 2023
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50 changes: 50 additions & 0 deletions perception/tracking_object_merger/CMakeLists.txt
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cmake_minimum_required(VERSION 3.8)
project(tracking_object_merger VERSION 1.0.0)

if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID MATCHES "Clang")
add_compile_options(-Wall -Wextra -Wpedantic -Werror -Wconversion)
endif()

find_package(autoware_cmake REQUIRED)
autoware_package()
find_package(nlohmann_json REQUIRED) # for debug


# find dependencies
find_package(eigen3_cmake_module REQUIRED)
find_package(Eigen3 REQUIRED)
# uncomment the following section in order to fill in
# further dependencies manually.
# find_package(<dependency> REQUIRED)

include_directories(
SYSTEM
${EIGEN3_INCLUDE_DIR}
)

ament_auto_add_library(mu_successive_shortest_path SHARED
src/data_association/mu_successive_shortest_path/mu_successive_shortest_path_wrapper.cpp
)

ament_auto_add_library(decorative_tracker_merger_node SHARED
src/data_association/data_association.cpp
src/decorative_tracker_merger.cpp
src/utils/utils.cpp
src/utils/tracker_state.cpp
)

target_link_libraries(decorative_tracker_merger_node
mu_successive_shortest_path
Eigen3::Eigen
nlohmann_json::nlohmann_json # for debug
)

rclcpp_components_register_node(decorative_tracker_merger_node
PLUGIN "tracking_object_merger::DecorativeTrackerMergerNode"
EXECUTABLE decorative_tracker_merger
)

ament_auto_package(INSTALL_TO_SHARE
launch
config
)
114 changes: 114 additions & 0 deletions perception/tracking_object_merger/README.md
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# Tracking Object Merger

## Purpose

This package try to merge two tracking objects from different sensor.

## Inner-workings / Algorithms

Merging tracking objects from different sensor is a combination of data association and state fusion algorithms.

Detailed process depends on the merger policy.

### decorative_tracker_merger

In decorative_tracker_merger, we assume there are dominant tracking objects and sub tracking objects.
The name `decorative` means that sub tracking objects are used to complement the main objects.

Usually the dominant tracking objects are from LiDAR and sub tracking objects are from Radar or Camera.

Here show the processing pipeline.

![decorative_tracker_merger](./image/decorative_tracker_merger.drawio.svg)

#### time sync

Sub object(Radar or Camera) often has higher frequency than dominant object(LiDAR). So we need to sync the time of sub object to dominant object.

![time sync](image/time_sync.drawio.svg)

#### data association

In the data association, we use the following rules to determine whether two tracking objects are the same object.

- gating
- `distance gate`: distance between two tracking objects
- `angle gate`: angle between two tracking objects
- `mahalanobis_distance_gate`: Mahalanobis distance between two tracking objects
- `min_iou_gate`: minimum IoU between two tracking objects
- `max_velocity_gate`: maximum velocity difference between two tracking objects
- score
- score used in matching is equivalent to the distance between two tracking objects

#### tracklet update

Sub tracking objects are merged into dominant tracking objects.

Depends on the tracklet input sensor state, we update the tracklet state with different rules.

| state\priority | 1st | 2nd | 3rd |
| -------------------------- | ------ | ----- | ------ |
| Kinematics except velocity | LiDAR | Radar | Camera |
| Forward velocity | Radar | LiDAR | Camera |
| Object classification | Camera | LiDAR | Radar |

#### tracklet management

We use the `existence_probability` to manage tracklet.

- When we create a new tracklet, we set the `existence_probability` to $p_{sensor}$ value.
- In each update with specific sensor, we set the `existence_probability` to $p_{sensor}$ value.
- When tracklet does not have update with specific sensor, we reduce the `existence_probability` by `decay_rate`
- Object can be published if `existence_probability` is larger than `publish_probability_threshold`
- Object will be removed if `existence_probability` is smaller than `remove_probability_threshold`

![tracklet_management](./image/tracklet_management.drawio.svg)

These parameter can be set in `config/decorative_tracker_merger.param.yaml`.

```yaml
tracker_state_parameter:
remove_probability_threshold: 0.3
publish_probability_threshold: 0.6
default_lidar_existence_probability: 0.7
default_radar_existence_probability: 0.6
default_camera_existence_probability: 0.6
decay_rate: 0.1
max_dt: 1.0
```
#### input/parameters
| topic name | message type | description |
| ------------------------------- | ----------------------------------------------- | ------------------------------------------------------------------------------------- |
| `~input/main_object` | `autoware_auto_perception_msgs::TrackedObjects` | Dominant tracking objects. Output will be published with this dominant object stamps. |
| `~input/sub_object` | `autoware_auto_perception_msgs::TrackedObjects` | Sub tracking objects. |
| `output/object` | `autoware_auto_perception_msgs::TrackedObjects` | Merged tracking objects. |
| `debug/interpolated_sub_object` | `autoware_auto_perception_msgs::TrackedObjects` | Interpolated sub tracking objects. |

Default parameters are set in [config/decorative_tracker_merger.param.yaml](./config/decorative_tracker_merger.param.yaml).

| parameter name | description | default value |
| ------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------- |
| `base_link_frame_id` | base link frame id. This is used to transform the tracking object. | "base_link" |
| `time_sync_threshold` | time sync threshold. If the time difference between two tracking objects is smaller than this value, we consider these two tracking objects are the same object. | 0.05 |
| `sub_object_timeout_sec` | sub object timeout. If the sub object is not updated for this time, we consider this object is not exist. | 0.5 |
| `main_sensor_type` | main sensor type. This is used to determine the dominant tracking object. | "lidar" |
| `sub_sensor_type` | sub sensor type. This is used to determine the sub tracking object. | "radar" |
| `tracker_state_parameter` | tracker state parameter. This is used to manage the tracklet. | |

- the detail of `tracker_state_parameter` is described in [tracklet management](#tracklet-management)

#### tuning

As explained in [tracklet management](#tracklet-management), this tracker merger tend to maintain the both input tracking objects.

If there are many false positive tracking objects,

- decrease `default_<sensor>_existence_probability` of that sensor
- increase `decay_rate`
- increase `publish_probability_threshold` to publish only reliable tracking objects

### equivalent_tracker_merger

This is future work.
168 changes: 168 additions & 0 deletions perception/tracking_object_merger/config/data_association_matrix.param.yaml
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/**:
ros__parameters:
lidar-lidar:
can_assign_matrix:
#UNKNOWN, CAR, TRUCK, BUS, TRAILER, MOTORBIKE, BICYCLE,PEDESTRIAN
[0, 0, 0, 0, 0, 0, 0, 0, #UNKNOWN
0, 1, 1, 1, 1, 0, 0, 0, #CAR
0, 1, 1, 1, 1, 0, 0, 0, #TRUCK
0, 1, 1, 1, 1, 0, 0, 0, #BUS
0, 1, 1, 1, 1, 0, 0, 0, #TRAILER
0, 0, 0, 0, 0, 1, 1, 1, #MOTORBIKE
0, 0, 0, 0, 0, 1, 1, 1, #BICYCLE
0, 0, 0, 0, 0, 1, 1, 1] #PEDESTRIAN

max_dist_matrix:
#UNKNOWN, CAR, TRUCK, BUS, TRAILER, MOTORBIKE, BICYCLE, PEDESTRIAN
[4.0, 4.0, 5.0, 5.0, 5.0, 2.0, 2.0, 2.0, #UNKNOWN
4.0, 2.0, 5.0, 5.0, 5.0, 1.0, 1.0, 1.0, #CAR
5.0, 5.0, 5.0, 5.0, 5.0, 1.0, 1.0, 1.0, #TRUCK
5.0, 5.0, 5.0, 5.0, 5.0, 1.0, 1.0, 1.0, #BUS
5.0, 5.0, 5.0, 5.0, 5.0, 1.0, 1.0, 1.0, #TRAILER
2.0, 1.0, 1.0, 1.0, 1.0, 3.0, 3.0, 3.0, #MOTORBIKE
2.0, 1.0, 1.0, 1.0, 1.0, 3.0, 3.0, 3.0, #BICYCLE
2.0, 1.0, 1.0, 1.0, 1.0, 3.0, 3.0, 2.0] #PEDESTRIAN

max_rad_matrix: # If value is greater than pi, it will be ignored.
#UNKNOWN, CAR, TRUCK, BUS, TRAILER MOTORBIKE, BICYCLE, PEDESTRIAN
[3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, #UNKNOWN
3.150, 1.047, 1.047, 1.047, 1.047, 3.150, 3.150, 3.150, #CAR
3.150, 1.047, 1.047, 1.047, 1.047, 3.150, 3.150, 3.150, #TRUCK
3.150, 1.047, 1.047, 1.047, 1.047, 3.150, 3.150, 3.150, #BUS
3.150, 1.047, 1.047, 1.047, 1.047, 3.150, 3.150, 3.150, #TRAILER
3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, #MOTORBIKE
3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, #BICYCLE
3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150] #PEDESTRIAN

max_velocity_diff_matrix: # Ignored when value is larger than 100.0
#UNKNOWN, CAR, TRUCK, BUS, TRAILER, MOTORBIKE, BICYCLE, PEDESTRIAN
[100.0, 100.0,100.0,100.0,100.0, 100.0, 100.0, 100.0, #UNKNOWN
100.0, 8.0, 8.0, 8.0, 8.0, 100.0, 100.0, 100.0, #CAR
100.0, 8.0, 8.0, 8.0, 8.0, 100.0, 100.0, 100.0, #TRUCK
100.0, 8.0, 8.0, 8.0, 8.0, 100.0, 100.0, 100.0, #BUS
100.0, 8.0, 8.0, 8.0, 8.0, 100.0, 100.0, 100.0, #TRAILER
100.0, 100.0,100.0,100.0,100.0, 100.0, 100.0, 100.0, #MOTORBIKE
100.0, 100.0,100.0,100.0,100.0, 100.0, 100.0, 100.0, #BICYCLE
100.0, 100.0,100.0,100.0,100.0, 100.0, 100.0, 100.0] #PEDESTRIAN

min_iou_matrix: # If value is negative, it will be ignored.
#UNKNOWN, CAR, TRUCK, BUS, TRAILER, MOTORBIKE, BICYCLE, PEDESTRIAN
[0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, #UNKNOWN
0.1, 0.3, 0.2, 0.2, 0.2, 0.1, 0.1, 0.1, #CAR
0.1, 0.2, 0.3, 0.3, 0.3, 0.1, 0.1, 0.1, #TRUCK
0.1, 0.2, 0.3, 0.3, 0.3, 0.1, 0.1, 0.1, #BUS
0.1, 0.2, 0.3, 0.3, 0.3, 0.1, 0.1, 0.1, #TRAILER
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, #MOTORBIKE
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, #BICYCLE
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1] #PEDESTRIAN

lidar-radar:
can_assign_matrix:
#UNKNOWN, CAR, TRUCK, BUS, TRAILER, MOTORBIKE, BICYCLE,PEDESTRIAN
[0, 0, 0, 0, 0, 0, 0, 0, #UNKNOWN
0, 1, 1, 1, 1, 0, 0, 0, #CAR
0, 1, 1, 1, 1, 0, 0, 0, #TRUCK
0, 1, 1, 1, 1, 0, 0, 0, #BUS
0, 1, 1, 1, 1, 0, 0, 0, #TRAILER
0, 0, 0, 0, 0, 1, 1, 1, #MOTORBIKE
0, 0, 0, 0, 0, 1, 1, 1, #BICYCLE
0, 0, 0, 0, 0, 1, 1, 1] #PEDESTRIAN

max_dist_matrix:
#UNKNOWN, CAR, TRUCK, BUS, TRAILER, MOTORBIKE, BICYCLE, PEDESTRIAN
[4.0, 4.0, 5.0, 5.0, 5.0, 3.5, 3.5, 3.5, #UNKNOWN
4.0, 5.5, 6.0, 6.0, 6.0, 1.0, 1.0, 1.0, #CAR
5.0, 6.0, 6.5, 6.5, 6.5, 1.0, 1.0, 1.0, #TRUCK
5.0, 6.0, 6.5, 6.5, 6.5, 1.0, 1.0, 1.0, #BUS
5.0, 6.0, 6.5, 6.5, 6.5, 1.0, 1.0, 1.0, #TRAILER
3.5, 1.0, 1.0, 1.0, 1.0, 3.0, 3.0, 3.0, #MOTORBIKE
3.5, 1.0, 1.0, 1.0, 1.0, 3.0, 3.0, 3.0, #BICYCLE
3.5, 1.0, 1.0, 1.0, 1.0, 3.0, 3.0, 3.5] #PEDESTRIAN

max_rad_matrix: # If value is greater than pi, it will be ignored.
#UNKNOWN, CAR, TRUCK, BUS, TRAILER MOTORBIKE, BICYCLE, PEDESTRIAN
[3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, #UNKNOWN
3.150, 1.047, 1.047, 1.047, 1.047, 3.150, 3.150, 3.150, #CAR
3.150, 1.047, 1.047, 1.047, 1.047, 3.150, 3.150, 3.150, #TRUCK
3.150, 1.047, 1.047, 1.047, 1.047, 3.150, 3.150, 3.150, #BUS
3.150, 1.047, 1.047, 1.047, 1.047, 3.150, 3.150, 3.150, #TRAILER
3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, #MOTORBIKE
3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, #BICYCLE
3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150] #PEDESTRIAN

max_velocity_diff_matrix: # Ignored when value is larger than 100.0
#UNKNOWN, CAR, TRUCK, BUS, TRAILER, MOTORBIKE, BICYCLE, PEDESTRIAN
[100.0, 100.0,100.0,100.0,100.0, 100.0, 100.0, 100.0, #UNKNOWN
100.0, 8.0, 8.0, 8.0, 8.0, 100.0, 100.0, 100.0, #CAR
100.0, 8.0, 8.0, 8.0, 8.0, 100.0, 100.0, 100.0, #TRUCK
100.0, 8.0, 8.0, 8.0, 8.0, 100.0, 100.0, 100.0, #BUS
100.0, 8.0, 8.0, 8.0, 8.0, 100.0, 100.0, 100.0, #TRAILER
100.0, 100.0,100.0,100.0,100.0, 100.0, 100.0, 100.0, #MOTORBIKE
100.0, 100.0,100.0,100.0,100.0, 100.0, 100.0, 100.0, #BICYCLE
100.0, 100.0,100.0,100.0,100.0, 100.0, 100.0, 100.0] #PEDESTRIAN

min_iou_matrix: # set all value to 0.0 to disable this constraint
#UNKNOWN, CAR, TRUCK, BUS, TRAILER, MOTORBIKE, BICYCLE, PEDESTRIAN
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #UNKNOWN
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #CAR
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #TRUCK
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #BUS
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #TRAILER
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #MOTORBIKE
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #BICYCLE
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] #PEDESTRIAN

radar-radar:
can_assign_matrix:
#UNKNOWN, CAR, TRUCK, BUS, TRAILER, MOTORBIKE, BICYCLE,PEDESTRIAN
[0, 0, 0, 0, 0, 0, 0, 0, #UNKNOWN
0, 1, 1, 1, 1, 0, 0, 0, #CAR
0, 1, 1, 1, 1, 0, 0, 0, #TRUCK
0, 1, 1, 1, 1, 0, 0, 0, #BUS
0, 1, 1, 1, 1, 0, 0, 0, #TRAILER
0, 0, 0, 0, 0, 1, 1, 1, #MOTORBIKE
0, 0, 0, 0, 0, 1, 1, 1, #BICYCLE
0, 0, 0, 0, 0, 1, 1, 1] #PEDESTRIAN

max_dist_matrix:
#UNKNOWN, CAR, TRUCK, BUS, TRAILER, MOTORBIKE, BICYCLE, PEDESTRIAN
[4.0, 4.0, 5.0, 5.0, 5.0, 3.5, 3.5, 3.5, #UNKNOWN
4.0, 7.0, 7.5, 7.5, 7.5, 1.0, 1.0, 1.0, #CAR
5.0, 7.5, 7.5, 7.5, 7.5, 1.0, 1.0, 1.0, #TRUCK
5.0, 7.5, 7.5, 7.5, 7.5, 1.0, 1.0, 1.0, #BUS
5.0, 7.5, 7.5, 7.5, 7.5, 1.0, 1.0, 1.0, #TRAILER
3.5, 1.0, 1.0, 1.0, 1.0, 3.0, 3.0, 3.0, #MOTORBIKE
3.5, 1.0, 1.0, 1.0, 1.0, 3.0, 3.0, 3.0, #BICYCLE
3.5, 1.0, 1.0, 1.0, 1.0, 3.0, 3.0, 3.5] #PEDESTRIAN
max_rad_matrix: # If value is greater than pi, it will be ignored.
#UNKNOWN, CAR, TRUCK, BUS, TRAILER MOTORBIKE, BICYCLE, PEDESTRIAN
[3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, #UNKNOWN
3.150, 1.047, 1.047, 1.047, 1.047, 3.150, 3.150, 3.150, #CAR
3.150, 1.047, 1.047, 1.047, 1.047, 3.150, 3.150, 3.150, #TRUCK
3.150, 1.047, 1.047, 1.047, 1.047, 3.150, 3.150, 3.150, #BUS
3.150, 1.047, 1.047, 1.047, 1.047, 3.150, 3.150, 3.150, #TRAILER
3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, #MOTORBIKE
3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, #BICYCLE
3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150, 3.150] #PEDESTRIAN

max_velocity_diff_matrix: # Ignored when value is larger than 100.0
#UNKNOWN, CAR, TRUCK, BUS, TRAILER, MOTORBIKE, BICYCLE, PEDESTRIAN
[100.0, 100.0,100.0,100.0,100.0, 100.0, 100.0, 100.0, #UNKNOWN
100.0, 8.0, 8.0, 8.0, 8.0, 100.0, 100.0, 100.0, #CAR
100.0, 8.0, 8.0, 8.0, 8.0, 100.0, 100.0, 100.0, #TRUCK
100.0, 8.0, 8.0, 8.0, 8.0, 100.0, 100.0, 100.0, #BUS
100.0, 8.0, 8.0, 8.0, 8.0, 100.0, 100.0, 100.0, #TRAILER
100.0, 100.0,100.0,100.0,100.0, 100.0, 100.0, 100.0, #MOTORBIKE
100.0, 100.0,100.0,100.0,100.0, 100.0, 100.0, 100.0, #BICYCLE
100.0, 100.0,100.0,100.0,100.0, 100.0, 100.0, 100.0] #PEDESTRIAN

min_iou_matrix: # set all value to 0.0 to disable this constraint
#UNKNOWN, CAR, TRUCK, BUS, TRAILER, MOTORBIKE, BICYCLE, PEDESTRIAN
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #UNKNOWN
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #CAR
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #TRUCK
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #BUS
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #TRAILER
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #MOTORBIKE
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, #BICYCLE
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] #PEDESTRIAN
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