measurement_conversion.hpp

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// Copyright 2020 Apex.AI, Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
 
 
#ifndef STATE_ESTIMATION_NODES__MEASUREMENT_CONVERSION_HPP_
#define STATE_ESTIMATION_NODES__MEASUREMENT_CONVERSION_HPP_
 
#include <state_estimation_nodes/measurement.hpp>
#include <motion_model/constant_acceleration.hpp>
#include <nav_msgs/msg/odometry.hpp>
#include <geometry_msgs/msg/pose_with_covariance_stamped.hpp>
#include <geometry_msgs/msg/twist_with_covariance_stamped.hpp>
#include <rclcpp/time.hpp>
#include <Eigen/Geometry>
 
namespace autoware
{
namespace prediction
{
 
using MeasurementPose = Measurement<common::types::float32_t,
    motion::motion_model::ConstantAcceleration::States::POSE_X,
    motion::motion_model::ConstantAcceleration::States::POSE_Y>;
 
using MeasurementPoseAndSpeed = Measurement<common::types::float32_t,
    motion::motion_model::ConstantAcceleration::States::POSE_X,
    motion::motion_model::ConstantAcceleration::States::POSE_Y,
    motion::motion_model::ConstantAcceleration::States::VELOCITY_X,
    motion::motion_model::ConstantAcceleration::States::VELOCITY_Y>;
 
using MeasurementSpeed = Measurement<common::types::float32_t,
    motion::motion_model::ConstantAcceleration::States::VELOCITY_X,
    motion::motion_model::ConstantAcceleration::States::VELOCITY_Y>;
 
template<typename MeasurementT, typename MessageT>
MeasurementT message_to_measurement(
  const MessageT &, const Eigen::Isometry3f &)
{
  static_assert(
    sizeof(MessageT) == -1,
    "You have to have a specialization for message_to_measurement() function!");
  // We only have this throw here to make linter happy as this is a non-void function.
  throw std::runtime_error("You have to have a specialization for message_to_measurement()!");
}
 
template<std::int32_t kStateDimentionality, typename FloatT>
static constexpr Eigen::Transform<
  FloatT, kStateDimentionality, Eigen::TransformTraits::Isometry> downscale_isometry(
  const Eigen::Transform<FloatT, 3, Eigen::TransformTraits::Isometry> & isometry)
{
  static_assert(kStateDimentionality <= 3, "We only handle scaling the isometry down.");
  using Isometry = Eigen::Transform<
    FloatT, kStateDimentionality, Eigen::TransformTraits::Isometry>;
  Isometry result{Isometry::Identity()};
  result.linear() = isometry.rotation()
    .template block<kStateDimentionality, kStateDimentionality>(0, 0);
  result.translation() = isometry.translation().topRows(kStateDimentionality);
  return result;
}
 
template<>
STATE_ESTIMATION_NODES_PUBLIC MeasurementPoseAndSpeed message_to_measurement(
  const nav_msgs::msg::Odometry & msg,
  const Eigen::Isometry3f & tf_world_message);
 
template<>
STATE_ESTIMATION_NODES_PUBLIC MeasurementSpeed message_to_measurement(
  const geometry_msgs::msg::TwistWithCovarianceStamped & msg,
  const Eigen::Isometry3f & tf_world_message);
 
template<>
STATE_ESTIMATION_NODES_PUBLIC MeasurementPose message_to_measurement(
  const geometry_msgs::msg::PoseWithCovarianceStamped & msg,
  const Eigen::Isometry3f & tf_world_message);
 
}  // namespace prediction
}  // namespace autoware
 
 
#endif  // STATE_ESTIMATION_NODES__MEASUREMENT_CONVERSION_HPP_