EigenFactorPoint.hpp

/* Copyright (c) 2022, Gonzalo Ferrer
 *
 * 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.
 *
 *
 * EigenFactorPoint.hpp
 *
 *  Created on: Oct 24, 2022
 *      Author: Gonzalo Ferrer
 *              g.ferrer@skoltech.ru
 *              Mobile Robotics Lab.
 */

#ifndef EIGENFACTORPOINT_HPP_
#define EIGENFACTORPOINT_HPP_


#include "mrob/factor.hpp"
#include "mrob/factors/EigenFactorPlane.hpp"
#include <unordered_map>
#include <deque>
#include <Eigen/StdVector>
#include "mrob/SE3.hpp"


namespace mrob{

class EigenFactorPoint: public EigenFactorPlane{
public:
    EigenFactorPoint(Factor::robustFactorType robust_type = Factor::robustFactorType::QUADRATIC);
    ~EigenFactorPoint() override = default;
    void evaluate_residuals() override;
    void evaluate_jacobians() override;
    void evaluate_chi2() override;


protected:
    //vector of residuals, and T*mu_i follows the same indexing than Jacobian and Hessian
    std::deque<Mat31, Eigen::aligned_allocator<Mat31>> r_,transformed_mu_;
    SE3 T_ini_inv_;

};

}
#endif /* EigenFactorPlane_HPP_ */