apollo::planning::DualVariableWarmStartOSQPInterface类 参考

#include <dual_variable_warm_start_osqp_interface.h>

apollo::planning::DualVariableWarmStartOSQPInterface 的协作图:

Public 成员函数
	DualVariableWarmStartOSQPInterface (size_t horizon, double ts, const Eigen::MatrixXd &ego, const Eigen::MatrixXi &obstacles_edges_num, const size_t obstacles_num, const Eigen::MatrixXd &obstacles_A, const Eigen::MatrixXd &obstacles_b, const Eigen::MatrixXd &xWS, const PlannerOpenSpaceConfig &planner_open_space_config)
virtual	~DualVariableWarmStartOSQPInterface ()=default
void	get_optimization_results (Eigen::MatrixXd *l_warm_up, Eigen::MatrixXd *n_warm_up) const
bool	optimize ()
void	assemble_P (std::vector< c_float > *P_data, std::vector< c_int > *P_indices, std::vector< c_int > *P_indptr)
void	assemble_constraint (std::vector< c_float > *A_data, std::vector< c_int > *A_indices, std::vector< c_int > *A_indptr)
void	assembleA (const int r, const int c, const std::vector< c_float > &P_data, const std::vector< c_int > &P_indices, const std::vector< c_int > &P_indptr)
void	check_solution (const Eigen::MatrixXd &l_warm_up, const Eigen::MatrixXd &n_warm_up)
	DualVariableWarmStartOSQPInterface (size_t horizon, double ts, const Eigen::MatrixXd &ego, const Eigen::MatrixXi &obstacles_edges_num, const size_t obstacles_num, const Eigen::MatrixXd &obstacles_A, const Eigen::MatrixXd &obstacles_b, const Eigen::MatrixXd &xWS, const DualVariableWarmStartConfig &DualVariableWarmStartConfig)

详细描述

在文件 dual_variable_warm_start_osqp_interface.h 第 37 行定义.

构造及析构函数说明

DualVariableWarmStartOSQPInterface() [1/2]

apollo::planning::DualVariableWarmStartOSQPInterface::DualVariableWarmStartOSQPInterface	(	size_t	horizon,
		double	ts,
		const Eigen::MatrixXd &	ego,
		const Eigen::MatrixXi &	obstacles_edges_num,
		const size_t	obstacles_num,
		const Eigen::MatrixXd &	obstacles_A,
		const Eigen::MatrixXd &	obstacles_b,
		const Eigen::MatrixXd &	xWS,
		const PlannerOpenSpaceConfig &	planner_open_space_config
	)

在文件 dual_variable_warm_start_osqp_interface.cc 第 32 行定义.

                                                                 :
        ts_(ts),
        ego_(ego),
        obstacles_edges_num_(obstacles_edges_num),
        obstacles_A_(obstacles_A),
        obstacles_b_(obstacles_b),
        xWS_(xWS) {
    ACHECK(horizon < std::numeric_limits<int>::max()) << "Invalid cast on horizon in open space planner";
    horizon_ = static_cast<int>(horizon);
    ACHECK(obstacles_num < std::numeric_limits<int>::max()) << "Invalid cast on obstacles_num in open space planner";
    obstacles_num_ = static_cast<int>(obstacles_num);
    w_ev_ = ego_(1, 0) + ego_(3, 0);
    l_ev_ = ego_(0, 0) + ego_(2, 0);
    g_ = {l_ev_ / 2, w_ev_ / 2, l_ev_ / 2, w_ev_ / 2};
    offset_ = (ego_(0, 0) + ego_(2, 0)) / 2 - ego_(2, 0);
    obstacles_edges_sum_ = obstacles_edges_num_.sum();
    l_start_index_ = 0;
    n_start_index_ = l_start_index_ + obstacles_edges_sum_ * (horizon_ + 1);
    l_warm_up_ = Eigen::MatrixXd::Zero(obstacles_edges_sum_, horizon_ + 1);
    n_warm_up_ = Eigen::MatrixXd::Zero(4 * obstacles_num_, horizon_ + 1);
 
    // get_nlp_info
    lambda_horizon_ = obstacles_edges_sum_ * (horizon_ + 1);
 
    miu_horizon_ = obstacles_num_ * 4 * (horizon_ + 1);
 
    // number of variables
    num_of_variables_ = lambda_horizon_ + miu_horizon_;
    // number of constraints
    num_of_constraints_ = 3 * obstacles_num_ * (horizon_ + 1) + num_of_variables_;
 
    min_safety_distance_ = planner_open_space_config.dual_variable_warm_start_config().min_safety_distance();
    check_mode_ = planner_open_space_config.dual_variable_warm_start_config().debug_osqp();
    osqp_config_ = planner_open_space_config.dual_variable_warm_start_config().osqp_config();
}

~DualVariableWarmStartOSQPInterface()

virtual apollo::planning::DualVariableWarmStartOSQPInterface::~DualVariableWarmStartOSQPInterface ( )

virtualdefault

DualVariableWarmStartOSQPInterface() [2/2]

apollo::planning::DualVariableWarmStartOSQPInterface::DualVariableWarmStartOSQPInterface	(	size_t	horizon,
		double	ts,
		const Eigen::MatrixXd &	ego,
		const Eigen::MatrixXi &	obstacles_edges_num,
		const size_t	obstacles_num,
		const Eigen::MatrixXd &	obstacles_A,
		const Eigen::MatrixXd &	obstacles_b,
		const Eigen::MatrixXd &	xWS,
		const DualVariableWarmStartConfig &	DualVariableWarmStartConfig
	)

在文件 dual_variable_warm_start_osqp_interface.cc 第 77 行定义.

                                                                        :
        ts_(ts),
        ego_(ego),
        obstacles_edges_num_(obstacles_edges_num),
        obstacles_A_(obstacles_A),
        obstacles_b_(obstacles_b),
        xWS_(xWS) {
    ACHECK(horizon < std::numeric_limits<int>::max()) << "Invalid cast on horizon in open space planner";
    horizon_ = static_cast<int>(horizon);
    ACHECK(obstacles_num < std::numeric_limits<int>::max()) << "Invalid cast on obstacles_num in open space planner";
    obstacles_num_ = static_cast<int>(obstacles_num);
    w_ev_ = ego_(1, 0) + ego_(3, 0);
    l_ev_ = ego_(0, 0) + ego_(2, 0);
    g_ = {l_ev_ / 2, w_ev_ / 2, l_ev_ / 2, w_ev_ / 2};
    offset_ = (ego_(0, 0) + ego_(2, 0)) / 2 - ego_(2, 0);
    obstacles_edges_sum_ = obstacles_edges_num_.sum();
    l_start_index_ = 0;
    n_start_index_ = l_start_index_ + obstacles_edges_sum_ * (horizon_ + 1);
    l_warm_up_ = Eigen::MatrixXd::Zero(obstacles_edges_sum_, horizon_ + 1);
    n_warm_up_ = Eigen::MatrixXd::Zero(4 * obstacles_num_, horizon_ + 1);
 
    // get_nlp_info
    lambda_horizon_ = obstacles_edges_sum_ * (horizon_ + 1);
 
    miu_horizon_ = obstacles_num_ * 4 * (horizon_ + 1);
 
    // number of variables
    num_of_variables_ = lambda_horizon_ + miu_horizon_;
    // number of constraints
    num_of_constraints_ = 3 * obstacles_num_ * (horizon_ + 1) + num_of_variables_;
 
    min_safety_distance_ = DualVariableWarmStartConfig.min_safety_distance();
    check_mode_ = DualVariableWarmStartConfig.debug_osqp();
    osqp_config_ = DualVariableWarmStartConfig.osqp_config();
}

成员函数说明

assemble_constraint()

void apollo::planning::DualVariableWarmStartOSQPInterface::assemble_constraint	(	std::vector< c_float > *	A_data,
		std::vector< c_int > *	A_indices,
		std::vector< c_int > *	A_indptr
	)

在文件 dual_variable_warm_start_osqp_interface.cc 第 409 行定义.

                                    {
    /*
     * The constraint matrix is as the form,
     *  |R' * A',   G'|, #: 2 * obstacles_num_ * (horizon_ + 1)
     *  |A * t - b, -g|, #: obstacles_num_ * (horizon_ + 1)
     *  |I,          0|, #: num_of_lambda
     *  |0,          I|, #: num_of_miu
     */
    int r1_index = 0;
    int r2_index = 2 * obstacles_num_ * (horizon_ + 1);
    int r3_index = 3 * obstacles_num_ * (horizon_ + 1);
    int r4_index = 3 * obstacles_num_ * (horizon_ + 1) + lambda_horizon_;
    int first_row_location = 0;
 
    // lambda variables
    for (int i = 0; i < horizon_ + 1; ++i) {
        int edges_counter = 0;
 
        Eigen::MatrixXd R(2, 2);
        R << cos(xWS_(2, i)), sin(xWS_(2, i)), sin(xWS_(2, i)), cos(xWS_(2, i));
 
        Eigen::MatrixXd t_trans(1, 2);
        t_trans << (xWS_(0, i) + cos(xWS_(2, i)) * offset_), (xWS_(1, i) + sin(xWS_(2, i)) * offset_);
 
        // assume: stationary obstacles
        for (int j = 0; j < obstacles_num_; ++j) {
            int current_edges_num = obstacles_edges_num_(j, 0);
            Eigen::MatrixXd Aj = obstacles_A_.block(edges_counter, 0, current_edges_num, 2);
            Eigen::MatrixXd bj = obstacles_b_.block(edges_counter, 0, current_edges_num, 1);
 
            Eigen::MatrixXd r1_block(2, current_edges_num);
            r1_block = R * Aj.transpose();
 
            Eigen::MatrixXd r2_block(1, current_edges_num);
            r2_block = t_trans * Aj.transpose() - bj.transpose();
 
            // insert into A matrix, col by col
            for (int k = 0; k < current_edges_num; ++k) {
                A_data->emplace_back(r1_block(0, k));
                A_indices->emplace_back(r1_index);
 
                A_data->emplace_back(r1_block(1, k));
                A_indices->emplace_back(r1_index + 1);
 
                A_data->emplace_back(r2_block(0, k));
                A_indices->emplace_back(r2_index);
 
                A_data->emplace_back(1.0);
                A_indices->emplace_back(r3_index);
                r3_index++;
 
                A_indptr->emplace_back(first_row_location);
                first_row_location += 4;
            }
 
            // Update index
            edges_counter += current_edges_num;
            r1_index += 2;
            r2_index += 1;
        }
    }
 
    // miu variables
    // G: ((1, 0, -1, 0), (0, 1, 0, -1))
    // g: g_
    r1_index = 0;
    r2_index = 2 * obstacles_num_ * (horizon_ + 1);
    for (int i = 0; i < horizon_ + 1; ++i) {
        for (int j = 0; j < obstacles_num_; ++j) {
            for (int k = 0; k < 4; ++k) {
                // update G
                if (k < 2) {
                    A_data->emplace_back(1.0);
                } else {
                    A_data->emplace_back(-1.0);
                }
                A_indices->emplace_back(r1_index + k % 2);
 
                // update g'
                A_data->emplace_back(-g_[k]);
                A_indices->emplace_back(r2_index);
 
                // update I
                A_data->emplace_back(1.0);
                A_indices->emplace_back(r4_index);
                r4_index++;
 
                // update col index
                A_indptr->emplace_back(first_row_location);
                first_row_location += 3;
            }
 
            // update index
            r1_index += 2;
            r2_index += 1;
        }
    }
 
    A_indptr->emplace_back(first_row_location);
 
    CHECK_EQ(A_data->size(), A_indices->size());
    CHECK_EQ(A_indptr->size(), static_cast<size_t>(num_of_variables_) + 1);
}

assemble_P()

void apollo::planning::DualVariableWarmStartOSQPInterface::assemble_P	(	std::vector< c_float > *	P_data,
		std::vector< c_int > *	P_indices,
		std::vector< c_int > *	P_indptr
	)

在文件 dual_variable_warm_start_osqp_interface.cc 第 345 行定义.

                                    {
    // the objective function is norm(A' * lambda)
    std::vector<c_float> P_tmp;
    int edges_counter = 0;
 
    for (int j = 0; j < obstacles_num_; ++j) {
        int current_edges_num = obstacles_edges_num_(j, 0);
        Eigen::MatrixXd Aj;
        Aj = obstacles_A_.block(edges_counter, 0, current_edges_num, 2);
        // Eigen::MatrixXd AAj(current_edges_num, current_edges_num);
        Aj = Aj * Aj.transpose();
 
        CHECK_EQ(current_edges_num, Aj.cols());
        CHECK_EQ(current_edges_num, Aj.rows());
 
        for (int c = 0; c < current_edges_num; ++c) {
            for (int r = 0; r < current_edges_num; ++r) {
                P_tmp.emplace_back(Aj(r, c));
            }
        }
 
        // Update index
        edges_counter += current_edges_num;
    }
 
    int l_index = l_start_index_;
    int first_row_location = 0;
    // the objective function is norm(A' * lambda)
    for (int i = 0; i < horizon_ + 1; ++i) {
        edges_counter = 0;
 
        for (auto item : P_tmp) {
            P_data->emplace_back(item);
        }
        // current assume: stationary obstacles
        for (int j = 0; j < obstacles_num_; ++j) {
            int current_edges_num = obstacles_edges_num_(j, 0);
 
            for (int c = 0; c < current_edges_num; ++c) {
                P_indptr->emplace_back(first_row_location);
                for (int r = 0; r < current_edges_num; ++r) {
                    P_indices->emplace_back(r + l_index);
                }
                first_row_location += current_edges_num;
            }
 
            // Update index
            edges_counter += current_edges_num;
            l_index += current_edges_num;
        }
    }
 
    CHECK_EQ(P_indptr->size(), static_cast<size_t>(lambda_horizon_));
    for (int i = lambda_horizon_; i < num_of_variables_ + 1; ++i) {
        P_indptr->emplace_back(first_row_location);
    }
 
    CHECK_EQ(P_data->size(), P_indices->size());
    CHECK_EQ(P_indptr->size(), static_cast<size_t>(num_of_variables_) + 1);
}

assembleA()

void apollo::planning::DualVariableWarmStartOSQPInterface::assembleA	(	const int	r,
		const int	c,
		const std::vector< c_float > &	P_data,
		const std::vector< c_int > &	P_indices,
		const std::vector< c_int > &	P_indptr
	)

在文件 dual_variable_warm_start_osqp_interface.cc 第 150 行定义.

                                          {
    constraint_A_ = Eigen::MatrixXf::Zero(r, c);
 
    for (size_t i = 0; i < P_indptr.size() - 1; ++i) {
        if (P_indptr[i] < 0 || P_indptr[i] >= static_cast<int>(P_indices.size())) {
            continue;
        }
 
        for (auto idx = P_indptr[i]; idx < P_indptr[i + 1]; ++idx) {
            int tmp_c = static_cast<int>(i);
            int tmp_r = static_cast<int>(P_indices[idx]);
            constraint_A_(tmp_r, tmp_c) = static_cast<float>(P_data[idx]);
        }
    }
}

check_solution()

void apollo::planning::DualVariableWarmStartOSQPInterface::check_solution	(	const Eigen::MatrixXd &	l_warm_up,
		const Eigen::MatrixXd &	n_warm_up
	)

在文件 dual_variable_warm_start_osqp_interface.cc 第 285 行定义.

                                        {
    Eigen::MatrixXf x(num_of_variables_, 1);
    Eigen::MatrixXf g(num_of_constraints_, 1);
 
    // extract primal results
    int variable_index = 0;
    // 1. lagrange constraint l, [0, obstacles_edges_sum_ - 1] * [0,
    // horizon_l
    for (int i = 0; i < horizon_ + 1; ++i) {
        for (int j = 0; j < obstacles_edges_sum_; ++j) {
            x(variable_index, 0) = static_cast<float>(l_warm_up(j, i));
            ++variable_index;
        }
    }
 
    // 2. lagrange constraint n, [0, 4*obstacles_num-1] * [0, horizon_]
    for (int i = 0; i < horizon_ + 1; ++i) {
        for (int j = 0; j < 4 * obstacles_num_; ++j) {
            x(variable_index, 0) = static_cast<float>(n_warm_up(j, i));
            ++variable_index;
        }
    }
 
    g = constraint_A_ * x;
    int r1_index = 0;
    int r2_index = 2 * obstacles_num_ * (horizon_ + 1);
    int r3_index = 3 * obstacles_num_ * (horizon_ + 1);
    int r4_index = 3 * obstacles_num_ * (horizon_ + 1) + lambda_horizon_;
 
    for (int idx = r1_index; idx < r2_index; ++idx) {
        if (std::abs(g(idx, 0)) > 1e-6) {
            AERROR << "G' * mu + R' * A * lambda == 0 constraint fails, "
                   << "constraint_index: " << idx << ", g: " << g(idx, 0);
        }
    }
 
    for (int idx = r2_index; idx < r3_index; ++idx) {
        if (g(idx, 0) < min_safety_distance_) {
            AERROR << "-g' * mu + (A * t - b) * lambda) >= d_min constraint fails, "
                   << "constraint_index: " << idx << ", g: " << g(idx, 0);
        }
    }
 
    for (int idx = r3_index; idx < r4_index; ++idx) {
        if (g(idx, 0) < 0) {
            AERROR << "lambda box constraint fails, "
                   << "constraint_index: " << idx << ", g: " << g(idx, 0);
        }
    }
 
    for (int idx = r4_index; idx < num_of_constraints_; ++idx) {
        if (g(idx, 0) < 0) {
            AERROR << "miu box constraint fails, "
                   << "constraint_index: " << idx << ", g: " << g(idx, 0);
        }
    }
}

get_optimization_results()

void apollo::planning::DualVariableWarmStartOSQPInterface::get_optimization_results	(	Eigen::MatrixXd *	l_warm_up,
		Eigen::MatrixXd *	n_warm_up
	)		const

在文件 dual_variable_warm_start_osqp_interface.cc 第 516 行定义.

                                        {
    *l_warm_up = l_warm_up_;
    *n_warm_up = n_warm_up_;
}

optimize()

bool apollo::planning::DualVariableWarmStartOSQPInterface::optimize

(

)

在文件 dual_variable_warm_start_osqp_interface.cc 第 171 行定义.

                                                  {
    int kNumParam = num_of_variables_;
    int kNumConst = num_of_constraints_;
 
    bool succ = true;
    // assemble P, quadratic term in objective
    std::vector<c_float> P_data;
    std::vector<c_int> P_indices;
    std::vector<c_int> P_indptr;
    assemble_P(&P_data, &P_indices, &P_indptr);
    if (check_mode_) {
        AINFO << "print P_data in whole: ";
        printMatrix(kNumParam, kNumParam, P_data, P_indices, P_indptr);
    }
    // assemble q, linear term in objective
    c_float q[kNumParam];
    for (int i = 0; i < kNumParam; ++i) {
        q[i] = 0.0;
    }
 
    // assemble A, linear term in constraints
    std::vector<c_float> A_data;
    std::vector<c_int> A_indices;
    std::vector<c_int> A_indptr;
    assemble_constraint(&A_data, &A_indices, &A_indptr);
    if (check_mode_) {
        AINFO << "print A_data in whole: ";
        printMatrix(kNumConst, kNumParam, A_data, A_indices, A_indptr);
        assembleA(kNumConst, kNumParam, A_data, A_indices, A_indptr);
    }
 
    // assemble lb & ub
    c_float lb[kNumConst];
    c_float ub[kNumConst];
    for (int i = 0; i < kNumConst; ++i) {
        lb[i] = 0.0;
        if (i >= 2 * obstacles_num_ * (horizon_ + 1) && i < 3 * obstacles_num_ * (horizon_ + 1)) {
            lb[i] = min_safety_distance_;
        }
        if (i < 2 * obstacles_num_ * (horizon_ + 1)) {
            ub[i] = 0.0;
        } else {
            ub[i] = 2e19;
        }
    }
 
    // Problem settings
    OSQPSettings* settings = reinterpret_cast<OSQPSettings*>(c_malloc(sizeof(OSQPSettings)));
 
    // Define Solver settings as default
    osqp_set_default_settings(settings);
    settings->alpha = osqp_config_.alpha();  // Change alpha parameter
    settings->eps_abs = osqp_config_.eps_abs();
    settings->eps_rel = osqp_config_.eps_rel();
    settings->max_iter = osqp_config_.max_iter();
    settings->polish = osqp_config_.polish();
    settings->verbose = osqp_config_.osqp_debug_log();
 
    // Populate data
    OSQPData* data = reinterpret_cast<OSQPData*>(c_malloc(sizeof(OSQPData)));
    data->n = kNumParam;
    data->m = kNumConst;
    data->P = csc_matrix(data->n, data->n, P_data.size(), P_data.data(), P_indices.data(), P_indptr.data());
    data->q = q;
    data->A = csc_matrix(data->m, data->n, A_data.size(), A_data.data(), A_indices.data(), A_indptr.data());
    data->l = lb;
    data->u = ub;
 
    // Workspace
    OSQPWorkspace* work = nullptr;
    // osqp_setup(&work, data, settings);
    work = osqp_setup(data, settings);
 
    // Solve Problem
    osqp_solve(work);
 
    // check state
    if (work->info->status_val != 1 && work->info->status_val != 2) {
        AWARN << "OSQP dual warm up unsuccess, "
              << "return status: " << work->info->status;
        succ = false;
    }
 
    // extract primal results
    int variable_index = 0;
    // 1. lagrange constraint l, [0, obstacles_edges_sum_ - 1] * [0,
    // horizon_l
    for (int i = 0; i < horizon_ + 1; ++i) {
        for (int j = 0; j < obstacles_edges_sum_; ++j) {
            l_warm_up_(j, i) = work->solution->x[variable_index];
            ++variable_index;
        }
    }
 
    // 2. lagrange constraint n, [0, 4*obstacles_num-1] * [0, horizon_]
    for (int i = 0; i < horizon_ + 1; ++i) {
        for (int j = 0; j < 4 * obstacles_num_; ++j) {
            n_warm_up_(j, i) = work->solution->x[variable_index];
            ++variable_index;
        }
    }
 
    succ = succ & (work->info->obj_val <= 1.0);
 
    // Cleanup
    osqp_cleanup(work);
    c_free(data->A);
    c_free(data->P);
    c_free(data);
    c_free(settings);
 
    return succ;
}

---

该类的文档由以下文件生成:

• modules/planning/planning_open_space/trajectory_smoother/dual_variable_warm_start_osqp_interface.h
• modules/planning/planning_open_space/trajectory_smoother/dual_variable_warm_start_osqp_interface.cc