Create y2024 localizer

This is primarily a copy of the y2023 localizer, with updates to
better characterize the noise of the april tag readings (by separating
out heading/distance/skew measurements).

It also listens to the drivetrain Position message for encoder readings
rather than relying on the IMU board to send them.

This adds a few things:
* The main localizer libraries and processes themselves.
* Updates to the AOS configs to pull in the appropriate localization
  channels.
* Creates the typescript plots for localization debugging.
* Creates some dummy camera extrinsics for use in the tests.

Change-Id: I58d5c1da0d3dc2dad98bd2a9fc10965db51c4f84
Signed-off-by: James Kuszmaul <jabukuszmaul+collab@gmail.com>
diff --git a/y2024/localizer/localizer.cc b/y2024/localizer/localizer.cc
new file mode 100644
index 0000000..30bb108
--- /dev/null
+++ b/y2024/localizer/localizer.cc
@@ -0,0 +1,605 @@
+#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/vision/target_map_utils.h"
+#include "y2024/constants.h"
+
+DEFINE_double(max_pose_error, 1e-6,
+              "Throw out target poses with a higher pose error than this");
+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, 1.0,
+              "Scale the target pose distortion factor by this when computing "
+              "the noise.");
+DEFINE_double(
+    max_implied_yaw_error, 3.0,
+    "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.");
+
+namespace y2024::localizer {
+namespace {
+constexpr std::array<std::string_view, Localizer::kNumCameras>
+    kDetectionChannels{"/orin1/camera0", "/orin1/camera1", "/orin2/camera0",
+                       "/orin2/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;
+}
+}  // 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_),
+      ekf_(dt_config_),
+      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")) {
+  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) {
+        // 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();
+        // Ecnoder 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(),
+            ekf_.P());
+      });
+
+  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(), ekf_.P());
+  });
+}
+
+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;
+  }
+  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) {
+  return target_poses_.count(target_id) != 0;
+}
+
+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;
+  }
+
+  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::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());
+
+  Eigen::Matrix3d R = Eigen::Matrix3d::Zero();
+  R.diagonal() = noises.cwiseAbs2();
+  if (debug_builder != nullptr) {
+    const Eigen::Vector3d camera_position =
+        corrector.observed_camera_pose().abs_pos();
+    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());
+    // 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);
+    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 (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().topRows<3>().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.
+  observations_.CorrectKnownH(
+      Eigen::Vector3d::Zero(), &U,
+      Corrector(state_at_capture.value(), H_field_target, H_robot_camera,
+                H_camera_target),
+      R, t_);
+  ++total_accepted_targets_;
+  ++cameras_.at(camera_index).total_accepted_targets;
+  VLOG(1) << "new state " << ekf_.X_hat().topRows<3>().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);
+  }
+}
+
+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());
+  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);
+  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_;
+}
+
+}  // namespace y2024::localizer