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How to add a new lidar detector algorithm

The processing flow of lidar perception module is shown below:

The detector algorithm introduced by this document is located at Detection Component listed below. Current architecture of Detection Component is shown： lidar detection high-level lidar detection

As we can see from above structure, lidar detector algorithm, such as PointPillars, is the derived class of base_lidar_detector which acts as a abstract class member of base_lidar_obstacle_detection located in Detection Component. Next, We will introduce how to add a new lidar detector algorithm.

Apollo has provided two lidar detector algorithms – PointPillars and CNN （NCut will no longer be updated）. Both of them could be easily changed or replaced by other algorithms. The input of algorithm should be original points cloud data, while the output should be obastacle object data. This document will introduce how to add a new lidar detector algorithm, the basic task sequence is listed below：

  1. Define a class that inherits base_lidar_detector

  2. Implement the class NewLidarDetector

  3. Add config and param proto file for NewLidarDetector

  4. Update lidar_obstacle_detection.conf

The steps are elaborated below for better understanding:

Define a class that inherits base_lidar_detector

All the lidar detector algorithms shall inherit base_lidar_detector，which defines a set of interfaces. Here is an example of the detector implementation:

namespace apollo {
namespace perception {
namespace lidar {

class NewLidarDetector : public BaseLidarDetector {
 public:
  NewLidarDetector();
  virtual ~NewLidarDetector() = default;

  bool Init(const LidarDetectorInitOptions& options = LidarDetectorInitOptions()) override;

  bool Detect(const LidarDetectorOptions& options, LidarFrame* frame) override;

  std::string Name() const override;

};  // class NewLidarDetector

}  // namespace lidar
}  // namespace perception
}  // namespace apollo

The function signature of base_lidar_detector is pre-defined：

struct LidarDetectorInitOptions {
  std::string sensor_name = "velodyne64";
};

struct LidarDetectorOptions {};

struct LidarFrame {
  // point cloud
  std::shared_ptr<base::AttributePointCloud<base::PointF>> cloud;
  // world point cloud
  std::shared_ptr<base::AttributePointCloud<base::PointD>> world_cloud;
  // timestamp
  double timestamp = 0.0;
  // lidar to world pose
  Eigen::Affine3d lidar2world_pose = Eigen::Affine3d::Identity();
  // lidar to world pose
  Eigen::Affine3d novatel2world_pose = Eigen::Affine3d::Identity();
  // hdmap struct
  std::shared_ptr<base::HdmapStruct> hdmap_struct = nullptr;
  // segmented objects
  std::vector<std::shared_ptr<base::Object>> segmented_objects;
  // tracked objects
  std::vector<std::shared_ptr<base::Object>> tracked_objects;
  // point cloud roi indices
  base::PointIndices roi_indices;
  // point cloud non ground indices
  base::PointIndices non_ground_indices;
  // secondary segmentor indices
  base::PointIndices secondary_indices;
  // sensor info
  base::SensorInfo sensor_info;
  // reserve string
  std::string reserve;

  void Reset();

  void FilterPointCloud(base::PointCloud<base::PointF> *filtered_cloud,
                        const std::vector<uint32_t> &indices);
};

Implement the class NewLidarDetector

To ensure the new detector could function properly, NewLidarDetector should at least override the interface Init(), Detect(), Name() defined in base_lidar_detector. Init() is resposible for config loading, class member initialization, etc. And Detect() will implement the basic logic of algorithm. A concrete NewLidarDetector.cc example is shown：

namespace apollo {
namespace perception {
namespace lidar {

bool NewLidarDetector::Init(const LidarDetectorInitOptions& options) {
    /*
    Initialization of your detector
    */
}

bool NewLidarDetector::Detect(const LidarDetectorOptions& options, LidarFrame* frame) {
    /*
    Implementation of your detector
    */
}

std::string NewLidarDetector::Name() const {
    /*
    Return your detector's name
    */
}

PERCEPTION_REGISTER_LIDARDETECTOR(NewLidarDetector); //register the new detector

}  // namespace lidar
}  // namespace perception
}  // namespace apollo

Add config and param proto file for NewLidarDetector

Follow the following steps to add config and param proto file for the new detector:

  1. Define a proto for the new detector configurations according to the requirements of your algorithm. As a reference， you can found and follow the proto definition of cnn_segmentation at modules/perception/lidar/lib/detector/cnn_segmentation/proto/cnnseg_config.proto

  2. Once finishing your proto, for example newlidardetector_config.proto, add the following content:

    syntax = "proto2";
package apollo.perception.lidar;

message NewLidarDetectorConfig {
    double parameter1 = 1;
    int32 parameter2 = 2;
}

  3. Define a proto for the new detector parameters according to the requirements of your algorithm. Also, as a reference, you can found and follow the proto definition of cnn_segmentation at modules/perception/lidar/lib/detector/cnn_segmentation/proto/cnnseg_param.proto. Similarly, add the following content once finished:

    syntax = "proto2";
package apollo.perception.lidar;

//your parameters

  4. Refer to modules/perception/production/conf/perception/lidar/config_manager.config and add your detector path:

    model_config_path: "./conf/perception/lidar/modules/newlidardetector_config.config"

  5. Refer to the modules/cnnseg.config in the same folder and create newlidardetector.config:

    model_configs {
    name: "NewLidarDetector"
    version: "1.0.0"
    string_params {
        name: "root_path"
        value: "./data/perception/lidar/models/newlidardetector"
    }
}

  6. Refer to cnnseg and create newlidardetector folder at modules/perception/production/data/perception/lidar/models/. Add .conf files for different sensors：

    Note：The "*.conf" and "*param.conf" file should have the same structure with the "proto" files defined in step 1，2，3.

Update lidar_obstacle_detection.conf

To use your new lidar detector algorithm in Apollo，you need to modify the value of detector to your detector’s name in lidar_obstacle_detection.conf located in corresponding sensor folder in modules/perception/production/data/perception/lidar/models/lidar_obstacle_pipline

Once you finished the above modifications, you new detector should take effect in Apollo.

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