diff --git a/include/basalt/vi_estimator/nfr_mapper.h b/include/basalt/vi_estimator/nfr_mapper.h index c458d12..e939ffa 100644 --- a/include/basalt/vi_estimator/nfr_mapper.h +++ b/include/basalt/vi_estimator/nfr_mapper.h @@ -205,5 +205,7 @@ class NfrMapper : public BundleAdjustmentBase { std::shared_ptr> hash_bow_database; VioConfig config; + + double lambda, min_lambda, max_lambda, lambda_vee; }; } // namespace basalt diff --git a/src/vi_estimator/nfr_mapper.cpp b/src/vi_estimator/nfr_mapper.cpp index fa4ebcd..88bcbb0 100644 --- a/src/vi_estimator/nfr_mapper.cpp +++ b/src/vi_estimator/nfr_mapper.cpp @@ -44,7 +44,11 @@ OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. namespace basalt { NfrMapper::NfrMapper(const Calibration& calib, const VioConfig& config) - : config(config) { + : config(config), + lambda(1e-10), + min_lambda(1e-32), + max_lambda(100), + lambda_vee(2) { this->calib = calib; this->obs_std_dev = config.mapper_obs_std_dev; this->huber_thresh = config.mapper_obs_huber_thresh; @@ -274,7 +278,7 @@ void NfrMapper::optimize(int num_iterations) { double error_total = rld_error + lopt.rel_error + lopt.roll_pitch_error; - std::cout << "iter " << iter + std::cout << "[LINEARIZE] iter " << iter << " before_update_error: vision: " << rld_error << " rel_error: " << lopt.rel_error << " roll_pitch_error: " << lopt.roll_pitch_error @@ -285,60 +289,103 @@ void NfrMapper::optimize(int num_iterations) { lopt.accum.setup_solver(); Eigen::VectorXd Hdiag = lopt.accum.Hdiagonal(); - Hdiag.setConstant(Hdiag.size(), 1e-6); - const Eigen::VectorXd inc = lopt.accum.solve(&Hdiag); + bool converged = false; + bool step = false; + int max_iter = 10; - // apply increment to poses - for (auto& kv : frame_poses) { - int idx = aom.abs_order_map.at(kv.first).first; - BASALT_ASSERT(!kv.second.isLinearized()); - kv.second.applyInc(-inc.segment(idx)); + while (!step && max_iter > 0 && !converged) { + Eigen::VectorXd Hdiag_lambda = Hdiag * lambda; + for (int i = 0; i < Hdiag_lambda.size(); i++) + Hdiag_lambda[i] = std::max(Hdiag_lambda[i], min_lambda); + + const Eigen::VectorXd inc = lopt.accum.solve(&Hdiag_lambda); + double max_inc = inc.array().abs().maxCoeff(); + if (max_inc < 1e-5) converged = true; + + backup(); + + // apply increment to poses + for (auto& kv : frame_poses) { + int idx = aom.abs_order_map.at(kv.first).first; + BASALT_ASSERT(!kv.second.isLinearized()); + kv.second.applyInc(-inc.segment(idx)); + } + + // Update points + tbb::blocked_range keys_range(0, rld_vec.size()); + auto update_points_func = [&](const tbb::blocked_range& r) { + for (size_t i = r.begin(); i != r.end(); ++i) { + const auto& rld = rld_vec[i]; + updatePoints(aom, rld, inc); + } + }; + tbb::parallel_for(keys_range, update_points_func); + + double after_update_vision_error = 0; + double after_rel_error = 0; + double after_roll_pitch_error = 0; + + computeError(after_update_vision_error); + computeRelPose(after_rel_error); + computeRollPitch(after_roll_pitch_error); + + double after_error_total = + after_update_vision_error + after_rel_error + after_roll_pitch_error; + + double f_diff = (error_total - after_error_total); + double l_diff = 0.5 * inc.dot(inc * lambda + lopt.accum.getB()); + + std::cout << "f_diff " << f_diff << " l_diff " << l_diff << std::endl; + + double step_quality = f_diff / l_diff; + + if (step_quality < 0) { + std::cout << "\t[REJECTED] lambda:" << lambda + << " step_quality: " << step_quality + << " max_inc: " << max_inc + << " vision_error: " << after_update_vision_error + << " rel_error: " << after_rel_error + << " roll_pitch_error: " << after_roll_pitch_error + << " total: " << after_error_total << std::endl; + lambda = std::min(max_lambda, lambda_vee * lambda); + lambda_vee *= 2; + + restore(); + } else { + std::cout << "\t[ACCEPTED] lambda:" << lambda + << " step_quality: " << step_quality + << " max_inc: " << max_inc + << " vision_error: " << after_update_vision_error + << " rel_error: " << after_rel_error + << " roll_pitch_error: " << after_roll_pitch_error + << " total: " << after_error_total << std::endl; + + lambda = std::max( + min_lambda, + lambda * + std::max(1.0 / 3, 1 - std::pow(2 * step_quality - 1, 3.0))); + lambda_vee = 2; + + step = true; + } + + max_iter--; + + if (after_error_total > error_total) { + std::cout << "increased error after update!!!" << std::endl; + } } - // Update points - tbb::blocked_range keys_range(0, rld_vec.size()); - auto update_points_func = [&](const tbb::blocked_range& r) { - for (size_t i = r.begin(); i != r.end(); ++i) { - const auto& rld = rld_vec[i]; - updatePoints(aom, rld, inc); - } - }; - tbb::parallel_for(keys_range, update_points_func); - - double after_update_vision_error = 0; - double after_rel_error = 0; - double after_roll_pitch_error = 0; - - computeError(after_update_vision_error); - computeRelPose(after_rel_error); - computeRollPitch(after_roll_pitch_error); - - double after_error_total = - after_update_vision_error + after_rel_error + after_roll_pitch_error; - - double error_diff = error_total - after_error_total; - auto t2 = std::chrono::high_resolution_clock::now(); - auto elapsed = std::chrono::duration_cast(t2 - t1); - std::cout << "iter " << iter - << " after_update_error: vision: " << after_update_vision_error - << " rel_error: " << after_rel_error - << " roll_pitch_error: " << after_roll_pitch_error - << " total: " << after_error_total << " max_inc " - << inc.array().abs().maxCoeff() << " error_diff " << error_diff - << " time : " << elapsed.count() << "(us), num_states " - << frame_states.size() << " num_poses " << frame_poses.size() - << std::endl; + std::cout << "iter " << iter << " time : " << elapsed.count() + << "(us), num_states " << frame_states.size() << " num_poses " + << frame_poses.size() << std::endl; - if (after_error_total > error_total) { - std::cout << "increased error after update!!!" << std::endl; - } - - if (inc.array().abs().maxCoeff() < 1e-4) break; + if (converged) break; // std::cerr << "LT\n" << LT << std::endl; // std::cerr << "z_p\n" << z_p.transpose() << std::endl; @@ -508,7 +555,8 @@ void NfrMapper::match_all() { // std::cout << "Closest frames for " << tcid << ": "; for (const auto& otcid_score : results) { - // std::cout << otcid_score.first << "(" << otcid_score.second << ") "; + // std::cout << otcid_score.first << "(" << otcid_score.second << ") + // "; if (otcid_score.first.frame_id != tcid.frame_id && otcid_score.second > config.mapper_frames_to_match_threshold) { match_pair m;