Ejemplo n.º 1
0
double SignedDistanceField::getDistanceAt(const Position3& position) const
{
  double xCenter = size_.x() / 2.0;
  double yCenter = size_.y() / 2.0;
  int i = std::round(xCenter - (position.x() - position_.x()) / resolution_);
  int j = std::round(yCenter - (position.y() - position_.y()) / resolution_);
  int k = std::round((position.z() - zIndexStartHeight_) / resolution_);
  i = std::max(i, 0);
  i = std::min(i, size_.x() - 1);
  j = std::max(j, 0);
  j = std::min(j, size_.y() - 1);
  k = std::max(k, 0);
  k = std::min(k, (int)data_.size() - 1);
  return data_[k](i, j);
}
Ejemplo n.º 2
0
Vector3 SignedDistanceField::getDistanceGradientAt(const Position3& position) const
{
  double xCenter = size_.x() / 2.0;
  double yCenter = size_.y() / 2.0;
  int i = std::round(xCenter - (position.x() - position_.x()) / resolution_);
  int j = std::round(yCenter - (position.y() - position_.y()) / resolution_);
  int k = std::round((position.z() - zIndexStartHeight_) / resolution_);
  i = std::max(i, 1);
  i = std::min(i, size_.x() - 2);
  j = std::max(j, 1);
  j = std::min(j, size_.y() - 2);
  k = std::max(k, 1);
  k = std::min(k, (int)data_.size() - 2);
  double dx = (data_[k](i - 1, j) - data_[k](i + 1, j)) / (2 * resolution_);
  double dy = (data_[k](i, j - 1) - data_[k](i, j + 1)) / (2 * resolution_);
  double dz = (data_[k + 1](i, j) - data_[k - 1](i, j)) / (2 * resolution_);
  return Vector3(dx, dy, dz);
}
Ejemplo n.º 3
0
double SignedDistanceField::getInterpolatedDistanceAt(const Position3& position) const
{
  double xCenter = size_.x() / 2.0;
  double yCenter = size_.y() / 2.0;
  int i = std::round(xCenter - (position.x() - position_.x()) / resolution_);
  int j = std::round(yCenter - (position.y() - position_.y()) / resolution_);
  int k = std::round((position.z() - zIndexStartHeight_) / resolution_);
  i = std::max(i, 0);
  i = std::min(i, size_.x() - 1);
  j = std::max(j, 0);
  j = std::min(j, size_.y() - 1);
  k = std::max(k, 0);
  k = std::min(k, (int)data_.size() - 1);
  Vector3 gradient = getDistanceGradientAt(position);
  double xp = position_.x() + ((size_.x() - i) - xCenter) * resolution_;
  double yp = position_.y() + ((size_.y() - j) - yCenter) * resolution_;
  double zp = zIndexStartHeight_ + k * resolution_;
  Vector3 error = position - Vector3(xp, yp, zp);
  return data_[k](i, j) + gradient.dot(error);
}
Ejemplo n.º 4
0
void GridMapRosConverter::toPointCloud(const grid_map::GridMap& gridMap,
                                       const std::vector<std::string>& layers,
                                       const std::string& pointLayer,
                                       sensor_msgs::PointCloud2& pointCloud)
{
  // Header.
  pointCloud.header.frame_id = gridMap.getFrameId();
  pointCloud.header.stamp.fromNSec(gridMap.getTimestamp());
  pointCloud.is_dense = false;

  // Fields.
  std::vector <std::string> fieldNames;

  for (const auto& layer : layers) {
    if (layer == pointLayer) {
      fieldNames.push_back("x");
      fieldNames.push_back("y");
      fieldNames.push_back("z");
    } else if (layer == "color") {
      fieldNames.push_back("rgb");
    } else {
      fieldNames.push_back(layer);
    }
  }

  pointCloud.fields.clear();
  pointCloud.fields.reserve(fieldNames.size());
  int offset = 0;

  for (auto& name : fieldNames) {
    sensor_msgs::PointField point_field;
    point_field.name = name;
    point_field.count = 1;
    point_field.datatype = sensor_msgs::PointField::FLOAT32;
    point_field.offset = offset;
    pointCloud.fields.push_back(point_field);
    offset = offset + point_field.count * 4;  // 4 for sensor_msgs::PointField::FLOAT32
  }

  // Resize.
  size_t nPoints = gridMap.getSize().prod();
  pointCloud.height = 1;
  pointCloud.width = nPoints;
  pointCloud.point_step = offset;
  pointCloud.row_step = pointCloud.width * pointCloud.point_step;
  pointCloud.data.resize(pointCloud.height * pointCloud.row_step);

  // Points.
  std::unordered_map<std::string, sensor_msgs::PointCloud2Iterator<float>> fieldIterators;
  for (auto& name : fieldNames) {
    fieldIterators.insert(
        std::pair<std::string, sensor_msgs::PointCloud2Iterator<float>>(
            name, sensor_msgs::PointCloud2Iterator<float>(pointCloud, name)));
  }

  GridMapIterator mapIterator(gridMap);

  for (size_t i = 0; i < nPoints; ++i) {
    Position3 position;
    position.setConstant(NAN);
    gridMap.getPosition3(pointLayer, *mapIterator, position);

    for (auto& iterator : fieldIterators) {
      if (iterator.first == "x") {
        *iterator.second = (float) position.x();
      } else if (iterator.first == "y") {
        *iterator.second = (float) position.y();
      } else if (iterator.first == "z") {
        *iterator.second = (float) position.z();
      } else if (iterator.first == "rgb") {
        *iterator.second = gridMap.at("color", *mapIterator);
      } else {
        *iterator.second = gridMap.at(iterator.first, *mapIterator);
      }
    }

    ++mapIterator;
    for (auto& iterator : fieldIterators) {
      ++iterator.second;
    }
  }
}
Ejemplo n.º 5
0
bool ElevationMap::add(const pcl::PointCloud<pcl::PointXYZRGB>::Ptr pointCloud, Eigen::VectorXf& pointCloudVariances, const ros::Time& timestamp, const Eigen::Affine3d& transformationSensorToMap)
{
  if (pointCloud->size() != pointCloudVariances.size()) {
    ROS_ERROR("ElevationMap::add: Size of point cloud (%i) and variances (%i) do not agree.",
              (int) pointCloud->size(), (int) pointCloudVariances.size());
    return false;
  }

  // Initialization for time calculation.
  const ros::WallTime methodStartTime(ros::WallTime::now());
  boost::recursive_mutex::scoped_lock scopedLockForRawData(rawMapMutex_);

  // Update initial time if it is not initialized.
  if (initialTime_.toSec() == 0) {
    initialTime_ = timestamp;
  }
  const double scanTimeSinceInitialization = (timestamp - initialTime_).toSec();

  for (unsigned int i = 0; i < pointCloud->size(); ++i) {
    auto& point = pointCloud->points[i];
    Index index;
    Position position(point.x, point.y);
    if (!rawMap_.getIndex(position, index)) continue; // Skip this point if it does not lie within the elevation map.

    auto& elevation = rawMap_.at("elevation", index);
    auto& variance = rawMap_.at("variance", index);
    auto& horizontalVarianceX = rawMap_.at("horizontal_variance_x", index);
    auto& horizontalVarianceY = rawMap_.at("horizontal_variance_y", index);
    auto& horizontalVarianceXY = rawMap_.at("horizontal_variance_xy", index);
    auto& color = rawMap_.at("color", index);
    auto& time = rawMap_.at("time", index);
    auto& lowestScanPoint = rawMap_.at("lowest_scan_point", index);
    auto& sensorXatLowestScan = rawMap_.at("sensor_x_at_lowest_scan", index);
    auto& sensorYatLowestScan = rawMap_.at("sensor_y_at_lowest_scan", index);
    auto& sensorZatLowestScan = rawMap_.at("sensor_z_at_lowest_scan", index);

    const float& pointVariance = pointCloudVariances(i);
    const float scanTimeSinceInitialization = (timestamp - initialTime_).toSec();

    if (!rawMap_.isValid(index)) {
      // No prior information in elevation map, use measurement.
      elevation = point.z;
      variance = pointVariance;
      horizontalVarianceX = minHorizontalVariance_;
      horizontalVarianceY = minHorizontalVariance_;
      horizontalVarianceXY = 0.0;
      colorVectorToValue(point.getRGBVector3i(), color);
      continue;
    }

    // Deal with multiple heights in one cell.
    const double mahalanobisDistance = fabs(point.z - elevation) / sqrt(variance);
    if (mahalanobisDistance > mahalanobisDistanceThreshold_) {
      if (scanTimeSinceInitialization - time <= scanningDuration_ && elevation > point.z) {
        // Ignore point if measurement is from the same point cloud (time comparison) and
        // if measurement is lower then the elevation in the map.
      } else if (scanTimeSinceInitialization - time <= scanningDuration_) {
        // If point is higher.
        elevation = point.z;
        variance = pointVariance;
      } else {
        variance += multiHeightNoise_;
      }
      continue;
    }

    // Store lowest points from scan for visibility checking.
    const float pointHeightPlusUncertainty = point.z + 3.0 * sqrt(pointVariance); // 3 sigma.
    if (std::isnan(lowestScanPoint) || pointHeightPlusUncertainty < lowestScanPoint){
      lowestScanPoint = pointHeightPlusUncertainty;
      const Position3 sensorTranslation(transformationSensorToMap.translation());
      sensorXatLowestScan = sensorTranslation.x();
      sensorYatLowestScan = sensorTranslation.y();
      sensorZatLowestScan = sensorTranslation.z();
    }

    // Fuse measurement with elevation map data.
    elevation = (variance * point.z + pointVariance * elevation) / (variance + pointVariance);
    variance = (pointVariance * variance) / (pointVariance + variance);
    // TODO Add color fusion.
    colorVectorToValue(point.getRGBVector3i(), color);
    time = scanTimeSinceInitialization;

    // Horizontal variances are reset.
    horizontalVarianceX = minHorizontalVariance_;
    horizontalVarianceY = minHorizontalVariance_;
    horizontalVarianceXY = 0.0;
  }

  clean();
  rawMap_.setTimestamp(timestamp.toNSec()); // Point cloud stores time in microseconds.

  const ros::WallDuration duration = ros::WallTime::now() - methodStartTime;
  ROS_INFO("Raw map has been updated with a new point cloud in %f s.", duration.toSec());
  return true;
}