| #include "y2024/localizer/localizer.h" |
| |
| #include "gflags/gflags.h" |
| |
| #include "aos/containers/sized_array.h" |
| #include "frc971/control_loops/drivetrain/localizer_generated.h" |
| #include "frc971/control_loops/pose.h" |
| #include "frc971/math/flatbuffers_matrix.h" |
| #include "frc971/vision/target_map_utils.h" |
| #include "y2024/constants.h" |
| |
| DEFINE_double(max_pose_error, 1e-5, |
| "Throw out target poses with a higher pose error than this"); |
| DEFINE_double(max_distortion, 0.1, ""); |
| DEFINE_double( |
| max_pose_error_ratio, 0.4, |
| "Throw out target poses with a higher pose error ratio than this"); |
| DEFINE_double(distortion_noise_scalar, 4.0, |
| "Scale the target pose distortion factor by this when computing " |
| "the noise."); |
| DEFINE_double( |
| max_implied_yaw_error, 5.0, |
| "Reject target poses that imply a robot yaw of more than this many degrees " |
| "off from our estimate."); |
| DEFINE_double( |
| max_implied_teleop_yaw_error, 30.0, |
| "Reject target poses that imply a robot yaw of more than this many degrees " |
| "off from our estimate."); |
| DEFINE_double(max_distance_to_target, 5.0, |
| "Reject target poses that have a 3d distance of more than this " |
| "many meters."); |
| DEFINE_double(max_auto_image_robot_speed, 2.0, |
| "Reject target poses when the robot is travelling faster than " |
| "this speed in auto."); |
| DEFINE_bool( |
| do_xytheta_corrections, true, |
| "If set, uses the x/y/theta corrector rather than a heading/distance/skew " |
| "one. This is better conditioned currently, but is theoretically worse due " |
| "to not capturing noise effectively."); |
| DEFINE_bool( |
| always_use_extra_tags, true, |
| "If set, we will use the \"deweighted\" tags even in auto mode (this " |
| "affects april tags whose field positions we do not trust as much)."); |
| |
| namespace y2024::localizer { |
| namespace { |
| constexpr std::array<std::string_view, Localizer::kNumCameras> |
| kDetectionChannels{"/orin1/camera0", "/orin1/camera1", "/imu/camera0", |
| "/imu/camera1"}; |
| |
| size_t CameraIndexForName(std::string_view name) { |
| for (size_t index = 0; index < kDetectionChannels.size(); ++index) { |
| if (name == kDetectionChannels.at(index)) { |
| return index; |
| } |
| } |
| LOG(FATAL) << "No camera channel named " << name; |
| } |
| |
| std::map<uint64_t, Localizer::Transform> GetTargetLocations( |
| const Constants &constants) { |
| CHECK(constants.has_common()); |
| CHECK(constants.common()->has_target_map()); |
| CHECK(constants.common()->target_map()->has_target_poses()); |
| std::map<uint64_t, Localizer::Transform> transforms; |
| for (const frc971::vision::TargetPoseFbs *target : |
| *constants.common()->target_map()->target_poses()) { |
| CHECK(target->has_id()); |
| CHECK(target->has_position()); |
| CHECK(target->has_orientation()); |
| CHECK_EQ(0u, transforms.count(target->id())); |
| transforms[target->id()] = PoseToTransform(target); |
| } |
| return transforms; |
| } |
| |
| // Returns the "nominal" covariance of localizer---i.e., the values to which it |
| // tends to converge during normal operation. By initializing the localizer's |
| // covariance this way, we reduce the likelihood that the first few corrections |
| // we receive will result in insane jumps in robot state. |
| Eigen::Matrix<double, Localizer::HybridEkf::kNStates, |
| Localizer::HybridEkf::kNStates> |
| NominalCovariance() { |
| Eigen::Matrix<double, Localizer::HybridEkf::kNStates, |
| Localizer::HybridEkf::kNStates> |
| P_transpose; |
| // Grabbed from when the robot was in a steady-state. |
| P_transpose << 0.00344391020344026, 2.78255540964953e-05, |
| -3.44257436790434e-09, 1.57165298196431e-09, 0.0207259965606711, |
| 1.57165298180587e-09, 0.0207259965606711, 0.054775354511474, |
| 0.0547753545094318, 3.6435938125014e-13, 0.0136249573295751, |
| -1.00705421392865e-05, 2.78255540964953e-05, 0.00107448929200992, |
| -7.42495169208041e-08, 1.85634700506266e-11, 0.000244343925617656, |
| 1.85634874205036e-11, 0.000244343925617656, 0.000645553479721632, |
| 0.000645553790286344, -3.98991820983687e-11, 0.000160471639203211, |
| 0.00085437373557969, -3.44257436791122e-09, -7.42495169208033e-08, |
| 8.84891122456971e-05, 5.60929454430362e-16, -3.19015358072956e-08, |
| 1.00798618104673e-15, -3.19015357689791e-08, 4.05905848804053e-07, |
| -5.37043312466153e-07, 2.59177623699213e-08, -3.54286115799832e-08, |
| -2.46295184320124e-07, 1.57165298196416e-09, 1.85634700506217e-11, |
| 5.60929459005148e-16, 4.99891338811926e-09, 3.59436612693873e-08, |
| 3.54690022095621e-18, 3.59436612693713e-08, 1.47025442116767e-07, |
| 1.47035806190949e-07, 4.66877989234937e-08, -1.08209016210542e-08, |
| -3.39984473837553e-14, 0.0207259965606711, 0.000244343925617655, |
| -3.19015358072649e-08, 3.59436612693935e-08, 0.301240404540565, |
| 3.59436612690168e-08, 0.301240404540535, 1.05741200222346, |
| 1.0574120022184, 8.29472747900822e-13, 0.138401597893958, |
| -1.43941751907531e-06, 1.57165298180564e-09, 1.85634874205096e-11, |
| 1.00798617244172e-15, 3.54690020212816e-18, 3.59436612690224e-08, |
| 4.99891338811924e-09, 3.59436612690048e-08, 1.4703580619019e-07, |
| 1.47025442115683e-07, -4.66877989234395e-08, -1.0820901621393e-08, |
| -3.40023588372784e-14, 0.0207259965606711, 0.000244343925617655, |
| -3.19015357689244e-08, 3.59436612693859e-08, 0.301240404540535, |
| 3.5943661269025e-08, 0.301240404540565, 1.05741200222289, |
| 1.05741200221897, 8.29752131358864e-13, 0.138401597893958, |
| -1.43941751907531e-06, 0.0547753545114739, 0.000645553479721628, |
| 4.05905848802199e-07, 1.4702544211661e-07, 1.05741200222346, |
| 1.47035806190016e-07, 1.05741200222289, 5.51003071369415, |
| 4.85571868991385, 3.11581831710161e-06, 0.388669918077443, |
| -2.97795819369728e-06, 0.054775354509432, 0.000645553790286345, |
| -5.37043312465425e-07, 1.47035806190839e-07, 1.0574120022184, |
| 1.47025442115792e-07, 1.05741200221897, 4.85571868991385, |
| 5.51003071367444, -3.11581462746269e-06, 0.388669918072973, |
| -2.97799067538699e-06, 3.64359250152554e-13, -3.98991820983e-11, |
| 2.5917762369921e-08, 4.66877989234987e-08, 8.2947423101614e-13, |
| -4.66877989234886e-08, 8.29754326977491e-13, 3.11581831710969e-06, |
| -3.11581462747612e-06, 0.212136173309098, 8.06835372350592e-13, |
| 8.80190080862899e-12, 0.0136249573295751, 0.000160471639203211, |
| -3.54286115799303e-08, -1.08209016210412e-08, 0.138401597893958, |
| -1.08209016213997e-08, 0.138401597893958, 0.388669918077444, |
| 0.388669918072972, 8.06834601598773e-13, 0.187427410345505, |
| -1.28632768080328e-06, -1.00705421392865e-05, 0.000854373735579689, |
| -2.46295184320122e-07, -3.39984473838037e-14, -1.4394175190755e-06, |
| -3.40023588373113e-14, -1.4394175190755e-06, -2.97795819369787e-06, |
| -2.9779906753875e-06, 8.80190080900245e-12, -1.28632768080338e-06, |
| 0.00381653175156393; |
| return P_transpose.transpose(); |
| } |
| } // namespace |
| |
| std::array<Localizer::CameraState, Localizer::kNumCameras> |
| Localizer::MakeCameras(const Constants &constants, aos::EventLoop *event_loop) { |
| CHECK(constants.has_cameras()); |
| std::array<Localizer::CameraState, Localizer::kNumCameras> cameras; |
| for (const CameraConfiguration *camera : *constants.cameras()) { |
| CHECK(camera->has_calibration()); |
| const frc971::vision::calibration::CameraCalibration *calibration = |
| camera->calibration(); |
| CHECK(!calibration->has_turret_extrinsics()) |
| << "The 2024 robot does not have cameras on a turret."; |
| CHECK(calibration->has_node_name()); |
| const std::string channel_name = |
| absl::StrFormat("/%s/camera%d", calibration->node_name()->string_view(), |
| calibration->camera_number()); |
| const size_t index = CameraIndexForName(channel_name); |
| // We default-construct the extrinsics matrix to all-zeros; use that to |
| // sanity-check whether we have populated the matrix yet or not. |
| CHECK(cameras.at(index).extrinsics.norm() == 0) |
| << "Got multiple calibrations for " |
| << calibration->node_name()->string_view(); |
| CHECK(calibration->has_fixed_extrinsics()); |
| cameras.at(index).extrinsics = |
| frc971::control_loops::drivetrain::FlatbufferToTransformationMatrix( |
| *calibration->fixed_extrinsics()); |
| cameras.at(index).debug_sender = |
| event_loop->MakeSender<VisualizationStatic>(channel_name); |
| } |
| for (const CameraState &camera : cameras) { |
| CHECK(camera.extrinsics.norm() != 0) << "Missing a camera calibration."; |
| } |
| return cameras; |
| } |
| |
| Localizer::Localizer(aos::EventLoop *event_loop) |
| : event_loop_(event_loop), |
| constants_fetcher_(event_loop), |
| dt_config_( |
| frc971::control_loops::drivetrain::DrivetrainConfig<double>:: |
| FromFlatbuffer(*CHECK_NOTNULL( |
| constants_fetcher_.constants().common()->drivetrain()))), |
| cameras_(MakeCameras(constants_fetcher_.constants(), event_loop)), |
| target_poses_(GetTargetLocations(constants_fetcher_.constants())), |
| down_estimator_(dt_config_), |
| // Force the dt to 1 ms (the nominal IMU frequency) since we have observed |
| // issues with timing on the orins. |
| // TODO(james): Ostensibly, we should be able to use the timestamps from |
| // the IMU board itself for exactly this; however, I am currently worried |
| // about the impacts of clock drift in using that. |
| ekf_(dt_config_, std::chrono::milliseconds(1)), |
| observations_(&ekf_), |
| xyz_observations_(&ekf_), |
| imu_watcher_(event_loop, dt_config_, |
| y2024::constants::Values::DrivetrainEncoderToMeters(1), |
| std::bind(&Localizer::HandleImu, this, std::placeholders::_1, |
| std::placeholders::_2, std::placeholders::_3, |
| std::placeholders::_4, std::placeholders::_5), |
| frc971::controls::ImuWatcher::TimestampSource::kPi), |
| utils_(event_loop), |
| status_sender_(event_loop->MakeSender<Status>("/localizer")), |
| output_sender_(event_loop->MakeSender<frc971::controls::LocalizerOutput>( |
| "/localizer")), |
| server_statistics_fetcher_( |
| event_loop_->MakeFetcher<aos::message_bridge::ServerStatistics>( |
| "/aos")), |
| client_statistics_fetcher_( |
| event_loop_->MakeFetcher<aos::message_bridge::ClientStatistics>( |
| "/aos")), |
| control_fetcher_(event_loop_->MakeFetcher< |
| frc971::control_loops::drivetrain::LocalizerControl>( |
| "/drivetrain")) { |
| if (dt_config_.is_simulated) { |
| down_estimator_.assume_perfect_gravity(); |
| } |
| |
| for (size_t camera_index = 0; camera_index < kNumCameras; ++camera_index) { |
| const std::string_view channel_name = kDetectionChannels.at(camera_index); |
| const aos::Channel *const channel = CHECK_NOTNULL( |
| event_loop->GetChannel<frc971::vision::TargetMap>(channel_name)); |
| event_loop->MakeWatcher( |
| channel_name, [this, channel, |
| camera_index](const frc971::vision::TargetMap &targets) { |
| CHECK(targets.has_target_poses()); |
| CHECK(targets.has_monotonic_timestamp_ns()); |
| const std::optional<aos::monotonic_clock::duration> clock_offset = |
| utils_.ClockOffset(channel->source_node()->string_view()); |
| if (!clock_offset.has_value()) { |
| VLOG(1) << "Rejecting image due to disconnected message bridge at " |
| << event_loop_->monotonic_now(); |
| cameras_.at(camera_index) |
| .rejection_counter.IncrementError( |
| RejectionReason::MESSAGE_BRIDGE_DISCONNECTED); |
| return; |
| } |
| const aos::monotonic_clock::time_point orin_capture_time( |
| std::chrono::nanoseconds(targets.monotonic_timestamp_ns()) - |
| clock_offset.value()); |
| if (orin_capture_time > event_loop_->context().monotonic_event_time) { |
| VLOG(1) << "Rejecting image due to being from future at " |
| << event_loop_->monotonic_now() << " with timestamp of " |
| << orin_capture_time << " and event time pf " |
| << event_loop_->context().monotonic_event_time; |
| cameras_.at(camera_index) |
| .rejection_counter.IncrementError( |
| RejectionReason::IMAGE_FROM_FUTURE); |
| return; |
| } |
| auto debug_builder = |
| cameras_.at(camera_index).debug_sender.MakeStaticBuilder(); |
| auto target_debug_list = debug_builder->add_targets(); |
| // The static_length should already be 20. |
| CHECK(target_debug_list->reserve(20)); |
| for (const frc971::vision::TargetPoseFbs *target : |
| *targets.target_poses()) { |
| VLOG(1) << "Handling target from " << camera_index; |
| HandleTarget(camera_index, orin_capture_time, *target, |
| target_debug_list->emplace_back()); |
| } |
| StatisticsForCamera(cameras_.at(camera_index), |
| debug_builder->add_statistics()); |
| debug_builder.CheckOk(debug_builder.Send()); |
| SendStatus(); |
| }); |
| } |
| |
| event_loop_->AddPhasedLoop([this](int) { SendOutput(); }, |
| std::chrono::milliseconds(20)); |
| |
| event_loop_->MakeWatcher( |
| "/drivetrain", |
| [this]( |
| const frc971::control_loops::drivetrain::LocalizerControl &control) { |
| HandleControl(control); |
| }); |
| |
| ekf_.set_ignore_accel(true); |
| // Priority should be lower than the imu reading process, but non-zero. |
| event_loop->SetRuntimeRealtimePriority(10); |
| event_loop->OnRun([this, event_loop]() { |
| ekf_.ResetInitialState(event_loop->monotonic_now(), |
| HybridEkf::State::Zero(), NominalCovariance()); |
| if (control_fetcher_.Fetch()) { |
| HandleControl(*control_fetcher_.get()); |
| } |
| }); |
| } |
| |
| void Localizer::HandleControl( |
| const frc971::control_loops::drivetrain::LocalizerControl &control) { |
| // This is triggered whenever we need to force the X/Y/(maybe theta) |
| // position of the robot to a particular point---e.g., during pre-match |
| // setup, or when commanded by a button on the driverstation. |
| |
| // For some forms of reset, we choose to keep our current yaw estimate |
| // rather than overriding it from the control message. |
| const double theta = control.keep_current_theta() |
| ? ekf_.X_hat(StateIdx::kTheta) |
| : control.theta(); |
| // Encoder values need to be reset based on the current values to ensure |
| // that we don't get weird corrections on the next encoder update. |
| const double left_encoder = ekf_.X_hat(StateIdx::kLeftEncoder); |
| const double right_encoder = ekf_.X_hat(StateIdx::kRightEncoder); |
| ekf_.ResetInitialState(t_, |
| (HybridEkf::State() << control.x(), control.y(), theta, |
| left_encoder, 0, right_encoder, 0, 0, 0, 0, 0, 0) |
| .finished(), |
| NominalCovariance()); |
| VLOG(1) << "Reset state"; |
| } |
| |
| void Localizer::HandleImu(aos::monotonic_clock::time_point /*sample_time_pico*/, |
| aos::monotonic_clock::time_point sample_time_orin, |
| std::optional<Eigen::Vector2d> /*encoders*/, |
| Eigen::Vector3d gyro, Eigen::Vector3d accel) { |
| std::optional<Eigen::Vector2d> encoders = utils_.Encoders(sample_time_orin); |
| last_encoder_readings_ = encoders; |
| // Ignore invalid readings; the HybridEkf will handle it reasonably. |
| if (!encoders.has_value()) { |
| return; |
| } |
| VLOG(1) << "Got encoders"; |
| if (t_ == aos::monotonic_clock::min_time) { |
| t_ = sample_time_orin; |
| } |
| if (t_ + 10 * frc971::controls::ImuWatcher::kNominalDt < sample_time_orin) { |
| t_ = sample_time_orin; |
| ++clock_resets_; |
| } |
| const aos::monotonic_clock::duration dt = sample_time_orin - t_; |
| t_ = sample_time_orin; |
| // We don't actually use the down estimator currently, but it's really |
| // convenient for debugging. |
| down_estimator_.Predict(gyro, accel, dt); |
| const double yaw_rate = (dt_config_.imu_transform * gyro)(2); |
| ekf_.UpdateEncodersAndGyro(encoders.value()(0), encoders.value()(1), yaw_rate, |
| utils_.VoltageOrZero(sample_time_orin), accel, t_); |
| SendStatus(); |
| } |
| |
| void Localizer::RejectImage(int camera_index, RejectionReason reason, |
| TargetEstimateDebugStatic *builder) { |
| if (builder != nullptr) { |
| builder->set_accepted(false); |
| builder->set_rejection_reason(reason); |
| } |
| cameras_.at(camera_index).rejection_counter.IncrementError(reason); |
| } |
| |
| // Only use april tags present in the target map; this method has also been used |
| // (in the past) for ignoring april tags that tend to produce problematic |
| // readings. |
| bool Localizer::UseAprilTag(uint64_t target_id) { |
| if (target_poses_.count(target_id) == 0) { |
| return false; |
| } |
| return true; |
| } |
| |
| bool Localizer::DeweightAprilTag(uint64_t target_id) { |
| const flatbuffers::Vector<uint64_t> *ignore_tags = nullptr; |
| |
| switch (utils_.Alliance()) { |
| case aos::Alliance::kRed: |
| ignore_tags = CHECK_NOTNULL( |
| constants_fetcher_.constants().common()->ignore_targets()->red()); |
| break; |
| case aos::Alliance::kBlue: |
| ignore_tags = CHECK_NOTNULL( |
| constants_fetcher_.constants().common()->ignore_targets()->blue()); |
| break; |
| case aos::Alliance::kInvalid: |
| return false; |
| } |
| return std::find(ignore_tags->begin(), ignore_tags->end(), target_id) != |
| ignore_tags->end(); |
| } |
| |
| namespace { |
| // Converts a camera transformation matrix from treating the +Z axis from |
| // pointing straight out the lens to having the +X pointing straight out the |
| // lens, with +Z going "up" (i.e., -Y in the normal convention) and +Y going |
| // leftwards (i.e., -X in the normal convention). |
| Localizer::Transform ZToXCamera(const Localizer::Transform &transform) { |
| return transform * |
| Eigen::Matrix4d{ |
| {0, -1, 0, 0}, {0, 0, -1, 0}, {1, 0, 0, 0}, {0, 0, 0, 1}}; |
| } |
| } // namespace |
| |
| void Localizer::HandleTarget( |
| int camera_index, const aos::monotonic_clock::time_point capture_time, |
| const frc971::vision::TargetPoseFbs &target, |
| TargetEstimateDebugStatic *debug_builder) { |
| ++total_candidate_targets_; |
| ++cameras_.at(camera_index).total_candidate_targets; |
| const uint64_t target_id = target.id(); |
| |
| if (debug_builder == nullptr) { |
| AOS_LOG(ERROR, "Dropped message from debug vector."); |
| } else { |
| debug_builder->set_camera(camera_index); |
| debug_builder->set_image_age_sec(aos::time::DurationInSeconds( |
| event_loop_->monotonic_now() - capture_time)); |
| debug_builder->set_image_monotonic_timestamp_ns( |
| std::chrono::duration_cast<std::chrono::nanoseconds>( |
| capture_time.time_since_epoch()) |
| .count()); |
| debug_builder->set_april_tag(target_id); |
| } |
| VLOG(2) << aos::FlatbufferToJson(&target); |
| if (!UseAprilTag(target_id)) { |
| VLOG(1) << "Rejecting target due to invalid ID " << target_id; |
| RejectImage(camera_index, RejectionReason::NO_SUCH_TARGET, debug_builder); |
| return; |
| } |
| double april_tag_noise_scalar = 1.0; |
| if (DeweightAprilTag(target_id)) { |
| if (!FLAGS_always_use_extra_tags && utils_.MaybeInAutonomous()) { |
| VLOG(1) << "Rejecting target due to auto invalid ID " << target_id; |
| RejectImage(camera_index, RejectionReason::NO_SUCH_TARGET, debug_builder); |
| return; |
| } else { |
| april_tag_noise_scalar = 10.0; |
| } |
| } |
| |
| const Transform &H_field_target = target_poses_.at(target_id); |
| const Transform &H_robot_camera = cameras_.at(camera_index).extrinsics; |
| |
| const Transform H_camera_target = PoseToTransform(&target); |
| |
| // In order to do the EKF correction, we determine the expected state based |
| // on the state at the time the image was captured; however, we insert the |
| // correction update itself at the current time. This is technically not |
| // quite correct, but saves substantial CPU usage & code complexity by |
| // making it so that we don't have to constantly rewind the entire EKF |
| // history. |
| const std::optional<State> state_at_capture = |
| ekf_.LastStateBeforeTime(capture_time); |
| |
| if (!state_at_capture.has_value()) { |
| VLOG(1) << "Rejecting image due to being too old."; |
| return RejectImage(camera_index, RejectionReason::IMAGE_TOO_OLD, |
| debug_builder); |
| } else if (target.pose_error() > FLAGS_max_pose_error) { |
| VLOG(1) << "Rejecting target due to high pose error " |
| << target.pose_error(); |
| return RejectImage(camera_index, RejectionReason::HIGH_POSE_ERROR, |
| debug_builder); |
| } else if (target.pose_error_ratio() > FLAGS_max_pose_error_ratio) { |
| VLOG(1) << "Rejecting target due to high pose error ratio " |
| << target.pose_error_ratio(); |
| return RejectImage(camera_index, RejectionReason::HIGH_POSE_ERROR_RATIO, |
| debug_builder); |
| } |
| |
| Corrector corrector(state_at_capture.value(), H_field_target, H_robot_camera, |
| H_camera_target); |
| const double distance_to_target = corrector.observed()(Corrector::kDistance); |
| |
| // Heading, distance, skew at 1 meter. |
| Eigen::Matrix<double, 3, 1> noises(0.01, 0.05, 0.05); |
| const double distance_noise_scalar = |
| std::min(1.0, std::pow(distance_to_target, 2.0)); |
| noises(Corrector::kDistance) *= distance_noise_scalar; |
| noises(Corrector::kSkew) *= distance_noise_scalar; |
| // TODO(james): This is leftover from last year; figure out if we want it. |
| // Scale noise by the distortion factor for this detection |
| noises *= (1.0 + FLAGS_distortion_noise_scalar * target.distortion_factor()); |
| noises *= april_tag_noise_scalar; |
| |
| Eigen::Matrix3d R = Eigen::Matrix3d::Zero(); |
| R.diagonal() = noises.cwiseAbs2(); |
| const Eigen::Vector3d camera_position = |
| corrector.observed_camera_pose().abs_pos(); |
| // Calculate the camera-to-robot transformation matrix ignoring the |
| // pitch/roll of the camera. |
| const Transform H_camera_robot_stripped = |
| frc971::control_loops::Pose(ZToXCamera(H_robot_camera)) |
| .AsTransformationMatrix() |
| .inverse(); |
| const frc971::control_loops::Pose measured_pose( |
| corrector.observed_camera_pose().AsTransformationMatrix() * |
| H_camera_robot_stripped); |
| if (debug_builder != nullptr) { |
| debug_builder->set_camera_x(camera_position.x()); |
| debug_builder->set_camera_y(camera_position.y()); |
| debug_builder->set_camera_theta( |
| corrector.observed_camera_pose().abs_theta()); |
| debug_builder->set_implied_robot_x(measured_pose.rel_pos().x()); |
| debug_builder->set_implied_robot_y(measured_pose.rel_pos().y()); |
| debug_builder->set_implied_robot_theta(measured_pose.rel_theta()); |
| |
| Corrector::PopulateMeasurement(corrector.expected(), |
| debug_builder->add_expected_observation()); |
| Corrector::PopulateMeasurement(corrector.observed(), |
| debug_builder->add_actual_observation()); |
| Corrector::PopulateMeasurement(noises, debug_builder->add_modeled_noise()); |
| } |
| |
| const double camera_yaw_error = |
| aos::math::NormalizeAngle(corrector.expected_camera_pose().abs_theta() - |
| corrector.observed_camera_pose().abs_theta()); |
| constexpr double kDegToRad = M_PI / 180.0; |
| |
| const double robot_speed = |
| (state_at_capture.value()(StateIdx::kLeftVelocity) + |
| state_at_capture.value()(StateIdx::kRightVelocity)) / |
| 2.0; |
| const double yaw_threshold = |
| (utils_.MaybeInAutonomous() ? FLAGS_max_implied_yaw_error |
| : FLAGS_max_implied_teleop_yaw_error) * |
| kDegToRad; |
| |
| if (target.distortion_factor() > FLAGS_max_distortion) { |
| VLOG(1) << "Rejecting target due to high distortion."; |
| return RejectImage(camera_index, RejectionReason::HIGH_DISTORTION, |
| debug_builder); |
| } else if (utils_.MaybeInAutonomous() && |
| (std::abs(robot_speed) > FLAGS_max_auto_image_robot_speed)) { |
| return RejectImage(camera_index, RejectionReason::ROBOT_TOO_FAST, |
| debug_builder); |
| } else if (std::abs(camera_yaw_error) > yaw_threshold) { |
| return RejectImage(camera_index, RejectionReason::HIGH_IMPLIED_YAW_ERROR, |
| debug_builder); |
| } else if (distance_to_target > FLAGS_max_distance_to_target) { |
| return RejectImage(camera_index, RejectionReason::HIGH_DISTANCE_TO_TARGET, |
| debug_builder); |
| } |
| |
| const Input U = ekf_.MostRecentInput(); |
| VLOG(1) << "previous state " << ekf_.X_hat().transpose(); |
| const State prior_state = ekf_.X_hat(); |
| // For the correction step, instead of passing in the measurement directly, |
| // we pass in (0, 0, 0) as the measurement and then for the expected |
| // measurement (Zhat) we calculate the error between the pose implied by |
| // the camera measurement and the current estimate of the |
| // pose. This doesn't affect any of the math, it just makes the code a bit |
| // more convenient to write given the Correct() interface we already have. |
| if (FLAGS_do_xytheta_corrections) { |
| Eigen::Vector3d Z(measured_pose.rel_pos().x(), measured_pose.rel_pos().y(), |
| measured_pose.rel_theta()); |
| Eigen::Matrix<double, 3, 1> xyz_noises(0.2, 0.2, 0.5); |
| xyz_noises *= distance_noise_scalar; |
| xyz_noises *= april_tag_noise_scalar; |
| // Scale noise by the distortion factor for this detection |
| xyz_noises *= |
| (1.0 + FLAGS_distortion_noise_scalar * target.distortion_factor()); |
| |
| Eigen::Matrix3d R_xyz = Eigen::Matrix3d::Zero(); |
| R_xyz.diagonal() = xyz_noises.cwiseAbs2(); |
| xyz_observations_.CorrectKnownH(Eigen::Vector3d::Zero(), &U, |
| XyzCorrector(state_at_capture.value(), Z), |
| R_xyz, t_); |
| } else { |
| observations_.CorrectKnownH(Eigen::Vector3d::Zero(), &U, corrector, R, t_); |
| } |
| ++total_accepted_targets_; |
| ++cameras_.at(camera_index).total_accepted_targets; |
| VLOG(1) << "new state " << ekf_.X_hat().transpose(); |
| if (debug_builder != nullptr) { |
| debug_builder->set_correction_x(ekf_.X_hat()(StateIdx::kX) - |
| prior_state(StateIdx::kX)); |
| debug_builder->set_correction_y(ekf_.X_hat()(StateIdx::kY) - |
| prior_state(StateIdx::kY)); |
| debug_builder->set_correction_theta(ekf_.X_hat()(StateIdx::kTheta) - |
| prior_state(StateIdx::kTheta)); |
| debug_builder->set_accepted(true); |
| debug_builder->set_expected_robot_x(ekf_.X_hat()(StateIdx::kX)); |
| debug_builder->set_expected_robot_y(ekf_.X_hat()(StateIdx::kY)); |
| debug_builder->set_expected_robot_theta(ekf_.X_hat()(StateIdx::kTheta)); |
| } |
| } |
| |
| void Localizer::SendOutput() { |
| auto builder = output_sender_.MakeBuilder(); |
| frc971::controls::LocalizerOutput::Builder output_builder = |
| builder.MakeBuilder<frc971::controls::LocalizerOutput>(); |
| output_builder.add_monotonic_timestamp_ns( |
| std::chrono::duration_cast<std::chrono::nanoseconds>( |
| event_loop_->context().monotonic_event_time.time_since_epoch()) |
| .count()); |
| output_builder.add_x(ekf_.X_hat(StateIdx::kX)); |
| output_builder.add_y(ekf_.X_hat(StateIdx::kY)); |
| output_builder.add_theta(ekf_.X_hat(StateIdx::kTheta)); |
| output_builder.add_zeroed(imu_watcher_.zeroer().Zeroed()); |
| output_builder.add_image_accepted_count(total_accepted_targets_); |
| const Eigen::Quaterniond &orientation = |
| Eigen::AngleAxis<double>(ekf_.X_hat(StateIdx::kTheta), |
| Eigen::Vector3d::UnitZ()) * |
| down_estimator_.X_hat(); |
| frc971::controls::Quaternion quaternion; |
| quaternion.mutate_x(orientation.x()); |
| quaternion.mutate_y(orientation.y()); |
| quaternion.mutate_z(orientation.z()); |
| quaternion.mutate_w(orientation.w()); |
| output_builder.add_orientation(&quaternion); |
| server_statistics_fetcher_.Fetch(); |
| client_statistics_fetcher_.Fetch(); |
| |
| bool orins_connected = true; |
| |
| if (server_statistics_fetcher_.get()) { |
| for (const auto *orin_server_status : |
| *server_statistics_fetcher_->connections()) { |
| if (orin_server_status->state() == |
| aos::message_bridge::State::DISCONNECTED) { |
| orins_connected = false; |
| } |
| } |
| } |
| |
| if (client_statistics_fetcher_.get()) { |
| for (const auto *pi_client_status : |
| *client_statistics_fetcher_->connections()) { |
| if (pi_client_status->state() == |
| aos::message_bridge::State::DISCONNECTED) { |
| orins_connected = false; |
| } |
| } |
| } |
| |
| // The output message is year-agnostic, and retains "pi" naming for histrocial |
| // reasons. |
| output_builder.add_all_pis_connected(orins_connected); |
| builder.CheckOk(builder.Send(output_builder.Finish())); |
| } |
| |
| flatbuffers::Offset<frc971::control_loops::drivetrain::LocalizerState> |
| Localizer::PopulateState(const State &X_hat, |
| flatbuffers::FlatBufferBuilder *fbb) { |
| frc971::control_loops::drivetrain::LocalizerState::Builder builder(*fbb); |
| builder.add_x(X_hat(StateIdx::kX)); |
| builder.add_y(X_hat(StateIdx::kY)); |
| builder.add_theta(X_hat(StateIdx::kTheta)); |
| builder.add_left_velocity(X_hat(StateIdx::kLeftVelocity)); |
| builder.add_right_velocity(X_hat(StateIdx::kRightVelocity)); |
| builder.add_left_encoder(X_hat(StateIdx::kLeftEncoder)); |
| builder.add_right_encoder(X_hat(StateIdx::kRightEncoder)); |
| builder.add_left_voltage_error(X_hat(StateIdx::kLeftVoltageError)); |
| builder.add_right_voltage_error(X_hat(StateIdx::kRightVoltageError)); |
| builder.add_angular_error(X_hat(StateIdx::kAngularError)); |
| builder.add_longitudinal_velocity_offset( |
| X_hat(StateIdx::kLongitudinalVelocityOffset)); |
| builder.add_lateral_velocity(X_hat(StateIdx::kLateralVelocity)); |
| return builder.Finish(); |
| } |
| |
| flatbuffers::Offset<ImuStatus> Localizer::PopulateImu( |
| flatbuffers::FlatBufferBuilder *fbb) const { |
| const auto zeroer_offset = imu_watcher_.zeroer().PopulateStatus(fbb); |
| const auto failures_offset = imu_watcher_.PopulateImuFailures(fbb); |
| ImuStatus::Builder builder(*fbb); |
| builder.add_zeroed(imu_watcher_.zeroer().Zeroed()); |
| builder.add_faulted_zero(imu_watcher_.zeroer().Faulted()); |
| builder.add_zeroing(zeroer_offset); |
| if (imu_watcher_.pico_offset().has_value()) { |
| builder.add_board_offset_ns(imu_watcher_.pico_offset().value().count()); |
| builder.add_board_offset_error_ns(imu_watcher_.pico_offset_error().count()); |
| } |
| if (last_encoder_readings_.has_value()) { |
| builder.add_left_encoder(last_encoder_readings_.value()(0)); |
| builder.add_right_encoder(last_encoder_readings_.value()(1)); |
| } |
| builder.add_imu_failures(failures_offset); |
| return builder.Finish(); |
| } |
| |
| flatbuffers::Offset<CumulativeStatistics> Localizer::StatisticsForCamera( |
| const CameraState &camera, flatbuffers::FlatBufferBuilder *fbb) { |
| const auto counts_offset = camera.rejection_counter.PopulateCounts(fbb); |
| CumulativeStatistics::Builder stats_builder(*fbb); |
| stats_builder.add_total_accepted(camera.total_accepted_targets); |
| stats_builder.add_total_candidates(camera.total_candidate_targets); |
| stats_builder.add_rejection_reasons(counts_offset); |
| return stats_builder.Finish(); |
| } |
| |
| void Localizer::StatisticsForCamera(const CameraState &camera, |
| CumulativeStatisticsStatic *builder) { |
| camera.rejection_counter.PopulateCountsStaticFbs( |
| builder->add_rejection_reasons()); |
| builder->set_total_accepted(camera.total_accepted_targets); |
| builder->set_total_candidates(camera.total_candidate_targets); |
| } |
| |
| void Localizer::SendStatus() { |
| auto builder = status_sender_.MakeBuilder(); |
| std::array<flatbuffers::Offset<CumulativeStatistics>, kNumCameras> |
| stats_offsets; |
| for (size_t ii = 0; ii < kNumCameras; ++ii) { |
| stats_offsets.at(ii) = StatisticsForCamera(cameras_.at(ii), builder.fbb()); |
| } |
| auto stats_offset = |
| builder.fbb()->CreateVector(stats_offsets.data(), stats_offsets.size()); |
| auto down_estimator_offset = |
| down_estimator_.PopulateStatus(builder.fbb(), t_); |
| auto imu_offset = PopulateImu(builder.fbb()); |
| auto state_offset = PopulateState(ekf_.X_hat(), builder.fbb()); |
| // covariance is a square; we use the number of rows in the state as the rows |
| // and cols of the covariance. |
| auto covariance_offset = |
| frc971::FromEigen<State::RowsAtCompileTime, State::RowsAtCompileTime>( |
| ekf_.P(), builder.fbb()); |
| Status::Builder status_builder = builder.MakeBuilder<Status>(); |
| status_builder.add_state(state_offset); |
| status_builder.add_down_estimator(down_estimator_offset); |
| status_builder.add_imu(imu_offset); |
| status_builder.add_statistics(stats_offset); |
| status_builder.add_ekf_covariance(covariance_offset); |
| builder.CheckOk(builder.Send(status_builder.Finish())); |
| } |
| |
| Eigen::Vector3d Localizer::Corrector::HeadingDistanceSkew( |
| const Pose &relative_pose) { |
| const double heading = relative_pose.heading(); |
| const double distance = relative_pose.xy_norm(); |
| const double skew = |
| ::aos::math::NormalizeAngle(relative_pose.rel_theta() - heading); |
| return {heading, distance, skew}; |
| } |
| |
| Localizer::Corrector Localizer::Corrector::CalculateHeadingDistanceSkewH( |
| const State &state_at_capture, const Transform &H_field_target, |
| const Transform &H_robot_camera, const Transform &H_camera_target) { |
| const Transform H_field_camera = H_field_target * H_camera_target.inverse(); |
| const Pose expected_robot_pose( |
| {state_at_capture(StateIdx::kX), state_at_capture(StateIdx::kY), 0.0}, |
| state_at_capture(StateIdx::kTheta)); |
| // Observed position on the field, reduced to just the 2-D pose. |
| const Pose observed_camera(ZToXCamera(H_field_camera)); |
| const Pose expected_camera(expected_robot_pose.AsTransformationMatrix() * |
| ZToXCamera(H_robot_camera)); |
| const Pose nominal_target(ZToXCamera(H_field_target)); |
| const Pose observed_target = nominal_target.Rebase(&observed_camera); |
| const Pose expected_target = nominal_target.Rebase(&expected_camera); |
| return Localizer::Corrector{ |
| expected_robot_pose, |
| observed_camera, |
| expected_camera, |
| HeadingDistanceSkew(expected_target), |
| HeadingDistanceSkew(observed_target), |
| frc971::control_loops::drivetrain::HMatrixForCameraHeadingDistanceSkew( |
| nominal_target, observed_camera)}; |
| } |
| |
| Localizer::Corrector::Corrector(const State &state_at_capture, |
| const Transform &H_field_target, |
| const Transform &H_robot_camera, |
| const Transform &H_camera_target) |
| : Corrector(CalculateHeadingDistanceSkewH( |
| state_at_capture, H_field_target, H_robot_camera, H_camera_target)) {} |
| |
| Localizer::Output Localizer::Corrector::H(const State &, const Input &) { |
| return expected_ - observed_; |
| } |
| |
| Localizer::Output Localizer::XyzCorrector::H(const State &, const Input &) { |
| CHECK(Z_.allFinite()); |
| Eigen::Vector3d Zhat = H_ * state_at_capture_ - Z_; |
| // Rewrap angle difference to put it back in range. |
| Zhat(2) = aos::math::NormalizeAngle(Zhat(2)); |
| VLOG(1) << "Zhat " << Zhat.transpose() << " Z_ " << Z_.transpose() |
| << " state " << (H_ * state_at_capture_).transpose(); |
| return Zhat; |
| } |
| |
| } // namespace y2024::localizer |