From 69ced787fbb81b7dbb451c7d8241836e8cac377a Mon Sep 17 00:00:00 2001 From: scepter914 Date: Fri, 30 May 2025 23:12:50 +0900 Subject: [PATCH 1/4] chore(perception): update perception document Signed-off-by: scepter914 --- .../clustering_based_detection.drawio.svg | 442 ++++++++++++++++++ .../image/motion_prediction.drawio.svg | 190 ++++++++ .../image/multi_object_tracking.drawio.svg | 267 +++++++++++ .../image/new_autoware_design.drawio.svg | 369 +++++++++++++++ .../image/priority_merger_1.drawio.svg | 241 ++++++++++ .../image/priority_merger_2.drawio.svg | 239 ++++++++++ .../perception/reference_implementation.md | 103 +++- 7 files changed, 1850 insertions(+), 1 deletion(-) create mode 100644 docs/design/autoware-architecture/perception/image/clustering_based_detection.drawio.svg create mode 100644 docs/design/autoware-architecture/perception/image/motion_prediction.drawio.svg create mode 100644 docs/design/autoware-architecture/perception/image/multi_object_tracking.drawio.svg create mode 100644 docs/design/autoware-architecture/perception/image/new_autoware_design.drawio.svg create mode 100644 docs/design/autoware-architecture/perception/image/priority_merger_1.drawio.svg create mode 100644 docs/design/autoware-architecture/perception/image/priority_merger_2.drawio.svg diff --git a/docs/design/autoware-architecture/perception/image/clustering_based_detection.drawio.svg b/docs/design/autoware-architecture/perception/image/clustering_based_detection.drawio.svg new file mode 100644 index 00000000000..07d1b1478ce --- /dev/null +++ b/docs/design/autoware-architecture/perception/image/clustering_based_detection.drawio.svg @@ -0,0 +1,442 @@ + + + + + + + + + + +
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+ + + Triggered b... + + + + + + + + + Text is not SVG - cannot display + + + + diff --git a/docs/design/autoware-architecture/perception/reference_implementation.md b/docs/design/autoware-architecture/perception/reference_implementation.md index 313471ae162..9a523daaecc 100644 --- a/docs/design/autoware-architecture/perception/reference_implementation.md +++ b/docs/design/autoware-architecture/perception/reference_implementation.md @@ -4,7 +4,7 @@ This document outlines detailed design of the reference imprementations. This allows developers and users to understand what is currently available with the Perception Component, how to utilize, expand, or add to its features. -## Architecture +## Whole architecture This diagram describes the architecture of the reference implementation. @@ -30,3 +30,104 @@ The Perception component consists of the following sub-components: - Ground filtered Point Cloud: A Point Cloud observed in the current frame, where the ground is removed. - **Occupancy Grid Map to Obstacle Segmentation** - Occupancy Grid Map: This is used for filtering outlier. + +## Architecture for object recognition + +![Overall Pipeline](image/new_autoware_design.drawio.svg) + +### Base 3D Detection + +Autoware primarily uses ML-based methods for 3D detection, referred to as **Base 3D Detection**. +Available methods include: + +- [CenterPoint](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_lidar_centerpoint) +- [TransFusion-L](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_lidar_transfusion) +- [BEVFusion-L](https://github.com/autowarefoundation/autoware_universe/tree/main/perception/autoware_bevfusion) +- [Apollo instance segmentation](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_lidar_apollo_instance_segmentation) + [shape estimation](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_shape_estimation) + +The detection range for `Base 3D Detection` typically falls between 90m and 120m, depending on the specific case. +If you wish to use Camera-LiDAR fusion, models like BEVFusion-CL (the model of Camera-LiDAR fusion) can be integrated. +However, since `Base 3D Detection` is a critical component of the new architecture, stable performance is essential. +Therefore, we do not recommend using Camera-LiDAR fusion methods in environments where sensor data frequently drops. + +### Near-Object 3D Detection + +As optional method for detection to enhance detection of nearby objects, especially pedestrians and cyclists, we have introduced **Near-Object 3D Detection**. +This can serve as a supplementary detection method alongside `Base 3D Detection`. + +We primarily use ML-based methods like CenterPoint for near-object detection, which excels at detecting small objects. +By applying higher-resolution voxel grids in the ML model, we improve detection accuracy for small objects. +The detection range typically falls between 30m and 50m. + +### (TBD) Camera-Only 3D Detection + +As optional method for detection to improve detection of objects that LiDAR-based methods struggle with, we have introduced **Camera-Only 3D Detection**. +`Camera-Only 3D detection` aims to solve the cases that are difficult to detect with LiDAR-based methods. +For example, `Camera-Only 3D detection` will deal with detection of objects with tree occlusion and long-distance recognition. + +Available methods include: + +- StreamPETR (TBD) + +Note that we will apply a high-confidence threshold to suppress the impact of false positives in `Camera-Only 3D Detection`. + +### Radar-Only Faraway Object 3D Detection + +For enhanced detection of distant objects, we use **Radar-Only 3D Detection**. +For more details, see [the document on faraway radar object detection](https://github.com/autowarefoundation/autoware-documentation/blob/main/docs/design/autoware-architecture/perception/reference-implementations/radar-based-3d-detector/faraway-object-detection.md). + +### (TBD) 3D Semantic Segmentation + +To improve detection of objects that are difficult to detect using traditional 3D detection methods, especially vegetation and traffic cone, we will implement **3D Semantic Segmentation**. +`3D Semantic Segmentation` provides non-ground point clouds and labeled pointcloud for some objects and vegetation. + +Available methods include: + +- FRNet (TBD) + +To integrate with the Autoware interface, we use a euclidean clustering method for processing 3D segmentation outputs. + +### Cluster-Based 3D Detection + +To enhance detection of objects that LiDAR-based methods may struggle with, we offer **Cluster-Based 3D Detection**. +`Cluster-Based 3D Detection` consists of many nodes, and the pipeline shows as following. + +![](image/clustering_based_detection.drawio.svg) + +`Cluster-Based 3D Detection` is based on euclidean clustering including roi based pointcloud fusion. +Its process combines non-ground LiDAR point clouds with the results of 2D detection or semantic segmentation. +This can be used as supplementary detection alongside `Base 3D Detection`. + +Note that as the data from point clouds and images increase, the processing time also increases. +Therefore, we recommend avoiding this pipeline in situations where processing time is critical or use for only narrow detection range. + +### Multi-Object Tracking v2 + +**Multi-Object Tracking v2** is based on existing [multi_object_tracker](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_multi_object_tracker) and illustrated below: + +![](image/multi_object_tracking.drawio.svg) + +The key features are as follows. + +- **Priority Object Merger** + +`Priority Object Merger` introduces new features compared to the existing [object_merger](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_object_merger). +`Priority Object Merger` can handle multiple inputs, reducing the need for multiple `object_merger` nodes. +It leads to be easy to debug. + +The existing `object_merger` uses approximate synchronization via message filters, introducing time delays. +As the amount of input data increases, which makes the delay, impacting the availability of autonomous driving. +Additionally, if some detections fail, the merger fails to combine the results, reducing availability. + +![](image/priority_merger_1.drawio.svg) + +The `Priority Object Merger` eliminates the message filter and uses a priority-based approach for the main detection. +When subscribing to the output of the main detection, it gathers all outputs from the detection pipeline. +It gathers outputs from all detections, ensuring that even if a secondary detection fails, results from other detections can still be merged, improving overall reliability and availability. + +![](image/priority_merger_2.drawio.svg) + +- **Stationary detection** + +As input data volume increases, processing time also increases. +To optimize performance, we reduce computational cost by incorporating stationary object detection. From fc658a661b43b1049f9f5656c1d724ce0278f3e1 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Fri, 30 May 2025 14:15:40 +0000 Subject: [PATCH 2/4] style(pre-commit): autofix --- .../clustering_based_detection.drawio.svg | 870 +++++++++--------- .../image/motion_prediction.drawio.svg | 377 ++++---- .../image/multi_object_tracking.drawio.svg | 531 +++++------ .../image/new_autoware_design.drawio.svg | 724 +++++++-------- .../image/priority_merger_1.drawio.svg | 471 +++++----- .../image/priority_merger_2.drawio.svg | 470 +++++----- 6 files changed, 1707 insertions(+), 1736 deletions(-) diff --git a/docs/design/autoware-architecture/perception/image/clustering_based_detection.drawio.svg b/docs/design/autoware-architecture/perception/image/clustering_based_detection.drawio.svg index 07d1b1478ce..c97c1e3f38f 100644 --- a/docs/design/autoware-architecture/perception/image/clustering_based_detection.drawio.svg +++ b/docs/design/autoware-architecture/perception/image/clustering_based_detection.drawio.svg @@ -1,442 +1,432 @@ - - - - - - - - - - -
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+
+
+ + Ground segmentation + + + + + + + + + + + Text is not SVG - cannot display + + diff --git a/docs/design/autoware-architecture/perception/image/motion_prediction.drawio.svg b/docs/design/autoware-architecture/perception/image/motion_prediction.drawio.svg index 5930804af24..4f970480ddf 100644 --- a/docs/design/autoware-architecture/perception/image/motion_prediction.drawio.svg +++ b/docs/design/autoware-architecture/perception/image/motion_prediction.drawio.svg @@ -1,190 +1,191 @@ - - - - - - - - - - -
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+ + Motion prediction + - - - - - Text is not SVG - cannot display - - - + + + + +
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+ Motion prediction +

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+ + Motion prediction + + + + + + +
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+ + Multi object tracking + + + + + + + + +
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+ + Merge results + +
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+ + Merge results + + + + + + +
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+ Dynamic objects +

+
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+ + Dynamic... + + + + + + +
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+ Static object +

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+ + Static... + + + + + + +
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+ Divide stationary object +
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+ + Divide stationary object + + + + + + + + + + + + +
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+ PredictedObjects +

+
+
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+ + Predicte... + + + + + + + Text is not SVG - cannot display + + diff --git a/docs/design/autoware-architecture/perception/image/multi_object_tracking.drawio.svg b/docs/design/autoware-architecture/perception/image/multi_object_tracking.drawio.svg index 013ed95f55e..0bc2a45b7f8 100644 --- a/docs/design/autoware-architecture/perception/image/multi_object_tracking.drawio.svg +++ b/docs/design/autoware-architecture/perception/image/multi_object_tracking.drawio.svg @@ -1,267 +1,268 @@ - - - - - - - - -
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+ Multi object tracking +

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+ Dynamic objects +

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+ Static objects +

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+ TrackedObject +

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- - - (optional) - -
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+ + (optional) +
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+ Labeled objects pointcloud +

+
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+ + Labeled object... + + + + + + +
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+ + Clustering-based 3D detection +
+ (optional) +
+ +
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+ + Clustering-based... + + + + + + + + + Text is not SVG - cannot display + + diff --git a/docs/design/autoware-architecture/perception/image/priority_merger_1.drawio.svg b/docs/design/autoware-architecture/perception/image/priority_merger_1.drawio.svg index f75e8abc44d..9069fad9abb 100644 --- a/docs/design/autoware-architecture/perception/image/priority_merger_1.drawio.svg +++ b/docs/design/autoware-architecture/perception/image/priority_merger_1.drawio.svg @@ -1,241 +1,234 @@ - - - - - - - -
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+ Base 3D detection +

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+ + Base 3D detection + - - - - - Text is not SVG - cannot display - - - + + + + + + +
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+ time +

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Data acquisition

+
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+ Cluster based 3D detection +

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+ Processing time +

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+ + Processing time + + + + + + +
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+ Merge and publish merged objects +

+
+
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+ + Merge and publish... + + + + + + + Text is not SVG - cannot display + + diff --git a/docs/design/autoware-architecture/perception/image/priority_merger_2.drawio.svg b/docs/design/autoware-architecture/perception/image/priority_merger_2.drawio.svg index 50b0ba42b04..6c258247db4 100644 --- a/docs/design/autoware-architecture/perception/image/priority_merger_2.drawio.svg +++ b/docs/design/autoware-architecture/perception/image/priority_merger_2.drawio.svg @@ -1,239 +1,235 @@ - - - - - - - -
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+ time +

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+
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+ Cluster based 3D detection +

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+ t +

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+ Triggered by priority detection result +

+
+
+
+ + Triggered b... + + + + + + + Text is not SVG - cannot display + + From 2b04d18a4e443423bee1111ba00afc5e6c9f5935 Mon Sep 17 00:00:00 2001 From: scepter914 Date: Wed, 4 Jun 2025 16:25:26 +0900 Subject: [PATCH 3/4] delete figure Signed-off-by: scepter914 --- .../image/motion_prediction.drawio.svg | 191 ------------------ 1 file changed, 191 deletions(-) delete mode 100644 docs/design/autoware-architecture/perception/image/motion_prediction.drawio.svg diff --git a/docs/design/autoware-architecture/perception/image/motion_prediction.drawio.svg b/docs/design/autoware-architecture/perception/image/motion_prediction.drawio.svg deleted file mode 100644 index 4f970480ddf..00000000000 --- a/docs/design/autoware-architecture/perception/image/motion_prediction.drawio.svg +++ /dev/null @@ -1,191 +0,0 @@ - - - - - - - - - - -
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- - Predicte... - - - - - - - Text is not SVG - cannot display - - - From 7ea3440317ebe2e54678322a852f8177bba4ce4e Mon Sep 17 00:00:00 2001 From: scepter914 Date: Wed, 4 Jun 2025 16:28:55 +0900 Subject: [PATCH 4/4] fix documents Signed-off-by: scepter914 --- .../perception/reference_implementation.md | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/docs/design/autoware-architecture/perception/reference_implementation.md b/docs/design/autoware-architecture/perception/reference_implementation.md index 9a523daaecc..a27730fbad3 100644 --- a/docs/design/autoware-architecture/perception/reference_implementation.md +++ b/docs/design/autoware-architecture/perception/reference_implementation.md @@ -2,7 +2,7 @@ ## Purpose of this document -This document outlines detailed design of the reference imprementations. This allows developers and users to understand what is currently available with the Perception Component, how to utilize, expand, or add to its features. +This document outlines detailed design of the reference implementations. This allows developers and users to understand what is currently available with the Perception Component, how to utilize, expand, or add to its features. ## Whole architecture @@ -65,10 +65,6 @@ As optional method for detection to improve detection of objects that LiDAR-base `Camera-Only 3D detection` aims to solve the cases that are difficult to detect with LiDAR-based methods. For example, `Camera-Only 3D detection` will deal with detection of objects with tree occlusion and long-distance recognition. -Available methods include: - -- StreamPETR (TBD) - Note that we will apply a high-confidence threshold to suppress the impact of false positives in `Camera-Only 3D Detection`. ### Radar-Only Faraway Object 3D Detection