parameter_estimator.hpp

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// Copyright 2018 the Autoware Foundation
//
// 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.
//
// Co-developed by Tier IV, Inc. and Apex.AI, Inc.
 
#ifndef MOTION_MODEL__PARAMETER_ESTIMATOR_HPP_
#define MOTION_MODEL__PARAMETER_ESTIMATOR_HPP_
 
#include <common/types.hpp>
#include <chrono>
#include "motion_model/motion_model.hpp"
 
using autoware::common::types::float32_t;
 
namespace autoware
{
namespace motion
{
namespace motion_model
{
 
template<int32_t NumStates>
class ParameterEstimator : public MotionModel<NumStates>
{
public:
  ParameterEstimator & operator=(const ParameterEstimator & rhs)
  {
    if (this != &rhs) {
      m_state = rhs.m_state;
    }
    return *this;
  }
  void predict(
    Eigen::Matrix<float32_t, NumStates, 1U> & x,
    const std::chrono::nanoseconds & dt) const override
  {
    // parameter estimators have no dynamics, so the values should not change over time
    (void)dt;
    x = m_state;
  }
  void predict(const std::chrono::nanoseconds & dt) override
  {
    // parameter estimators have no dynamics, so the values should not change over time
    (void)dt;
    // Nothing to do!
  }
  void compute_jacobian(
    Eigen::Matrix<float32_t, NumStates, NumStates> & F,
    const std::chrono::nanoseconds & dt) override
  {
    (void)dt;
    // identity
    F.setIdentity();
  }
  void compute_jacobian_and_predict(
    Eigen::Matrix<float32_t, NumStates, NumStates> & F,
    const std::chrono::nanoseconds & dt) override
  {
    compute_jacobian(F, dt);
    // no prediction!
  }
  float32_t operator[](const motion_model::index_t idx) const override
  {
    return m_state(idx);
  }
  void reset(const Eigen::Matrix<float32_t, NumStates, 1U> & x) override
  {
    m_state = x;
  }
  const Eigen::Matrix<float32_t, NumStates, 1U> & get_state() const override
  {
    return m_state;
  }
 
private:
  Eigen::Matrix<float32_t, NumStates, 1U> m_state;  
};  // class MotionModel
}  // namespace motion_model
}  // namespace motion
}  // namespace autoware
 
 
#endif  // MOTION_MODEL__PARAMETER_ESTIMATOR_HPP_