common.cpp

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/*      Title     : utils.cpp
 *      Project   : moveit_servo
 *      Created   : 05/17/2023
 *      Author    : Andy Zelenak, V Mohammed Ibrahim
 */
 
#include <moveit_servo/utils/common.hpp>
 
namespace
{
// The threshold above which `override_velocity_scaling_factor` will be used instead of computing the scaling from joint bounds.
constexpr double SCALING_OVERRIDE_THRESHOLD = 0.01;
 
// The angle threshold in radians below which a rotation will be considered the identity.
constexpr double MIN_ANGLE_THRESHOLD = 1E-16;
 
// The publishing frequency for the planning scene monitor, in Hz.
constexpr double PLANNING_SCENE_PUBLISHING_FREQUENCY = 25.0;
}  // namespace
 
namespace moveit_servo
{
 
std::optional<std::string> getIKSolverBaseFrame(const moveit::core::RobotStatePtr& robot_state,
                                                const std::string& group_name)
{
  const auto ik_solver = robot_state->getJointModelGroup(group_name)->getSolverInstance();
 
  if (ik_solver)
  {
    return ik_solver->getBaseFrame();
  }
  else
  {
    return std::nullopt;
  }
}
 
std::optional<std::string> getIKSolverTipFrame(const moveit::core::RobotStatePtr& robot_state,
                                               const std::string& group_name)
{
  const auto ik_solver = robot_state->getJointModelGroup(group_name)->getSolverInstance();
 
  if (ik_solver)
  {
    return ik_solver->getTipFrame();
  }
  else
  {
    return std::nullopt;
  }
}
 
bool isValidCommand(const Eigen::VectorXd& command)
{
  // returns true only if there are no nan values.
  return command.allFinite();
}
 
bool isValidCommand(const Eigen::Isometry3d& command)
{
  Eigen::Matrix3d identity, rotation;
  identity.setIdentity();
  rotation = command.linear();
  // checks rotation, will fail if there is nan
  const bool is_valid_rotation = rotation.allFinite() && identity.isApprox(rotation.inverse() * rotation);
  // Command is not vald if there is Nan
  const bool is_valid_translation = isValidCommand(command.translation());
  return is_valid_rotation && is_valid_translation;
}
 
bool isValidCommand(const TwistCommand& command)
{
  return !command.frame_id.empty() && isValidCommand(command.velocities);
}
 
bool isValidCommand(const PoseCommand& command)
{
  return !command.frame_id.empty() && isValidCommand(command.pose);
}
 
geometry_msgs::msg::Pose poseFromCartesianDelta(const Eigen::VectorXd& delta_x,
                                                const Eigen::Isometry3d& base_to_tip_frame_transform)
{
  // Get a transformation matrix with the desired position change
  Eigen::Isometry3d tf_pos_delta(Eigen::Isometry3d::Identity());
  tf_pos_delta.translate(Eigen::Vector3d(delta_x[0], delta_x[1], delta_x[2]));
 
  // Get a transformation matrix with desired orientation change
  Eigen::Isometry3d tf_rot_delta(Eigen::Isometry3d::Identity());
  const Eigen::Vector3d rot_vec = delta_x.block<3, 1>(3, 0, 3, 1);
  double angle = rot_vec.norm();
  if (angle > MIN_ANGLE_THRESHOLD)
  {
    const Eigen::Quaterniond q(Eigen::AngleAxisd(angle, rot_vec / angle).toRotationMatrix());
    tf_rot_delta.rotate(q);
  }
 
  // Find the new tip link position without newly applied rotation
  const Eigen::Isometry3d tf_no_new_rot = tf_pos_delta * base_to_tip_frame_transform;
 
  // we want the rotation to be applied in the requested reference frame,
  // but we want the rotation to be about the EE point in space, not the origin.
  // So, we need to translate to origin, rotate, then translate back
  // Given T = transformation matrix from origin -> EE point in space (translation component of tf_no_new_rot)
  // and T' as the opposite transformation, EE point in space -> origin (translation only)
  // apply final transformation as T * R * T' * tf_no_new_rot
  Eigen::Isometry3d tf_neg_translation = Eigen::Isometry3d::Identity();  // T'
  tf_neg_translation.translation() = -1 * tf_no_new_rot.translation();
  Eigen::Isometry3d tf_pos_translation = Eigen::Isometry3d::Identity();  // T
  tf_pos_translation.translation() = tf_no_new_rot.translation();
 
  // T * R * T' * tf_no_new_rot
  return tf2::toMsg(tf_pos_translation * tf_rot_delta * tf_neg_translation * tf_no_new_rot);
}
 
std::optional<trajectory_msgs::msg::JointTrajectory>
composeTrajectoryMessage(const servo::Params& servo_params, const std::deque<KinematicState>& joint_cmd_rolling_window)
{
  if (joint_cmd_rolling_window.size() < MIN_POINTS_FOR_TRAJ_MSG)
  {
    return {};
  }
 
  trajectory_msgs::msg::JointTrajectory joint_trajectory;
 
  joint_trajectory.joint_names = joint_cmd_rolling_window.front().joint_names;
  joint_trajectory.points.reserve(joint_cmd_rolling_window.size() + 1);
  joint_trajectory.header.stamp = joint_cmd_rolling_window.front().time_stamp;
 
  auto add_point = [servo_params](trajectory_msgs::msg::JointTrajectory& joint_trajectory, const KinematicState& state) {
    trajectory_msgs::msg::JointTrajectoryPoint point;
    size_t num_joints = state.positions.size();
    point.positions.reserve(num_joints);
    point.velocities.reserve(num_joints);
    point.accelerations.reserve(num_joints);
    if (servo_params.publish_joint_positions)
    {
      for (const auto& pos : state.positions)
      {
        point.positions.emplace_back(pos);
      }
    }
    if (servo_params.publish_joint_velocities)
    {
      for (const auto& vel : state.velocities)
      {
        point.velocities.emplace_back(vel);
      }
    }
    if (servo_params.publish_joint_accelerations)
    {
      for (const auto& acc : state.accelerations)
      {
        point.accelerations.emplace_back(acc);
      }
    }
    point.time_from_start = state.time_stamp - joint_trajectory.header.stamp;
    joint_trajectory.points.emplace_back(point);
  };
 
  for (size_t i = 0; i < joint_cmd_rolling_window.size() - 1; ++i)
  {
    add_point(joint_trajectory, joint_cmd_rolling_window[i]);
  }
 
  return joint_trajectory;
}
 
void updateSlidingWindow(KinematicState& next_joint_state, std::deque<KinematicState>& joint_cmd_rolling_window,
                         double max_expected_latency, const rclcpp::Time& cur_time)
{
  // remove commands older than current time minus the length of the sliding window
  next_joint_state.time_stamp = cur_time + rclcpp::Duration::from_seconds(max_expected_latency);
  const auto active_time_window = rclcpp::Duration::from_seconds(max_expected_latency);
  while (!joint_cmd_rolling_window.empty() &&
         joint_cmd_rolling_window.front().time_stamp < (cur_time - active_time_window))
  {
    joint_cmd_rolling_window.pop_front();
  }
 
  // remove commands at end of window if timestamp is the same as current command
  while (!joint_cmd_rolling_window.empty() && next_joint_state.time_stamp == joint_cmd_rolling_window.back().time_stamp)
  {
    joint_cmd_rolling_window.pop_back();
  }
 
  // update velocity: the velocity has the potential to dramatically influence interpolation of splines and causes large
  // overshooting. To alleviate this effect, the target velocity will be set to zero if the motion changes direction,
  // otherwise, it will calculate the forward and backward finite difference velocities and choose the minimum.
  if (joint_cmd_rolling_window.size() >= 2)
  {
    size_t num_points = joint_cmd_rolling_window.size();
    auto& last_state = joint_cmd_rolling_window[num_points - 1];
    auto& second_last_state = joint_cmd_rolling_window[num_points - 2];
 
    Eigen::VectorXd direction_1 = second_last_state.positions - last_state.positions;
    Eigen::VectorXd direction_2 = next_joint_state.positions - last_state.positions;
    Eigen::VectorXd signs = (direction_1.array().sign() - direction_2.array().sign()).round();
    for (long i = 0; i < last_state.velocities.size(); ++i)
    {
      // check if the direction have changed. `signs` will either have -2, +2 meaning a flat line, -1, 1 meaning a
      // rotated L shape, or 0 meaning a v-shape.
      if (signs[i] == 0.0)
      {
        // direction changed
        last_state.velocities[i] = 0;
      }
      else
      {
        const double delta_time_1 = (next_joint_state.time_stamp - last_state.time_stamp).seconds();
        const double delta_time_2 = (last_state.time_stamp - second_last_state.time_stamp).seconds();
        const auto velocity_1 = (next_joint_state.positions[i] - last_state.positions[i]) / delta_time_1;
        const auto velocity_2 = (last_state.positions[i] - second_last_state.positions[i]) / delta_time_2;
        last_state.velocities[i] = (std::abs(velocity_1) < std::abs(velocity_2)) ? velocity_1 : velocity_2;
      }
      next_joint_state.velocities[i] = last_state.velocities[i];
    }
  }
 
  // add next command
  joint_cmd_rolling_window.push_back(next_joint_state);
}
 
std_msgs::msg::Float64MultiArray composeMultiArrayMessage(const servo::Params& servo_params,
                                                          const KinematicState& joint_state)
{
  std_msgs::msg::Float64MultiArray multi_array;
  const size_t num_joints = joint_state.joint_names.size();
  multi_array.data.resize(num_joints);
  if (servo_params.publish_joint_positions)
  {
    for (size_t i = 0; i < num_joints; ++i)
    {
      multi_array.data[i] = joint_state.positions[i];
    }
  }
  else if (servo_params.publish_joint_velocities)
  {
    for (size_t i = 0; i < num_joints; ++i)
    {
      multi_array.data[i] = joint_state.velocities[i];
    }
  }
 
  return multi_array;
}
 
std::pair<double, StatusCode> velocityScalingFactorForSingularity(const moveit::core::RobotStatePtr& robot_state,
                                                                  const Eigen::VectorXd& target_delta_x,
                                                                  const servo::Params& servo_params)
{
  // We need to send information back about if we are halting, moving away or towards the singularity.
  StatusCode servo_status = StatusCode::NO_WARNING;
 
  const moveit::core::JointModelGroup* joint_model_group =
      robot_state->getJointModelGroup(servo_params.move_group_name);
 
  // Get the thresholds.
  const double lower_singularity_threshold = servo_params.lower_singularity_threshold;
  const double hard_stop_singularity_threshold = servo_params.hard_stop_singularity_threshold;
  const double leaving_singularity_threshold_multiplier = servo_params.leaving_singularity_threshold_multiplier;
 
  // Get size of total controllable dimensions.
  const size_t dims = target_delta_x.size();
 
  // Get the current Jacobian and compute SVD
  const Eigen::JacobiSVD<Eigen::MatrixXd> current_svd = Eigen::JacobiSVD<Eigen::MatrixXd>(
      robot_state->getJacobian(joint_model_group), Eigen::ComputeThinU | Eigen::ComputeThinV);
  const Eigen::MatrixXd matrix_s = current_svd.singularValues().asDiagonal();
 
  // Compute pseudo inverse
  const Eigen::MatrixXd pseudo_inverse = current_svd.matrixV() * matrix_s.inverse() * current_svd.matrixU().transpose();
 
  // Get the singular vector corresponding to least singular value.
  // This vector represents the least responsive dimension. By convention this is the last column of the matrix U.
  // The sign of the singular vector from result of SVD is not reliable, so we need to do extra checking to make sure of
  // the sign. See R. Bro, "Resolving the Sign Ambiguity in the Singular Value Decomposition".
  Eigen::VectorXd vector_towards_singularity = current_svd.matrixU().col(dims - 1);
 
  // Compute the current condition number. The ratio of max and min singular values.
  // By convention these are the first and last element of the diagonal.
  const double current_condition_number = current_svd.singularValues()(0) / current_svd.singularValues()(dims - 1);
 
  // Take a small step in the direction of vector_towards_singularity
  const Eigen::VectorXd delta_x = vector_towards_singularity * servo_params.singularity_step_scale;
 
  // Compute the new joint angles if we take the small step delta_x
  Eigen::VectorXd next_joint_angles;
  robot_state->copyJointGroupPositions(joint_model_group, next_joint_angles);
  next_joint_angles += pseudo_inverse * delta_x;
 
  // Compute the Jacobian SVD for the new robot state.
  robot_state->setJointGroupPositions(joint_model_group, next_joint_angles);
  const Eigen::JacobiSVD<Eigen::MatrixXd> next_svd = Eigen::JacobiSVD<Eigen::MatrixXd>(
      robot_state->getJacobian(joint_model_group), Eigen::ComputeThinU | Eigen::ComputeThinV);
 
  // Compute condition number for the new Jacobian.
  const double next_condition_number = next_svd.singularValues()(0) / next_svd.singularValues()(dims - 1);
 
  // If the condition number has increased, we are moving towards singularity and the direction of the
  // vector_towards_singularity is correct. If the condition number has decreased, it means the sign of
  // vector_towards_singularity needs to be flipped.
  if (next_condition_number <= current_condition_number)
  {
    vector_towards_singularity *= -1;
  }
 
  // Double check the direction using dot product.
  const bool moving_towards_singularity = vector_towards_singularity.dot(target_delta_x) > 0;
 
  // Compute upper condition variable threshold based on if we are moving towards or away from singularity.
  // See https://github.com/ros-planning/moveit2/pull/620#issuecomment-1201418258 for visual explanation.
  double upper_threshold;
  if (moving_towards_singularity)
  {
    upper_threshold = hard_stop_singularity_threshold;
  }
  else
  {
    const double threshold_size = (hard_stop_singularity_threshold - lower_singularity_threshold);
    upper_threshold = lower_singularity_threshold + (threshold_size * leaving_singularity_threshold_multiplier);
  }
 
  // Compute the scale based on the current condition number.
  double velocity_scale = 1.0;
  const bool is_above_lower_limit = current_condition_number > lower_singularity_threshold;
  const bool is_below_hard_stop_limit = current_condition_number < hard_stop_singularity_threshold;
  if (is_above_lower_limit && is_below_hard_stop_limit)
  {
    velocity_scale -=
        (current_condition_number - lower_singularity_threshold) / (upper_threshold - lower_singularity_threshold);
 
    servo_status = moving_towards_singularity ? StatusCode::DECELERATE_FOR_APPROACHING_SINGULARITY :
                                                StatusCode::DECELERATE_FOR_LEAVING_SINGULARITY;
  }
  // If condition number has crossed hard stop limit, halt the robot.
  else if (!is_below_hard_stop_limit)
  {
    servo_status = StatusCode::HALT_FOR_SINGULARITY;
    velocity_scale = 0.0;
  }
 
  return std::make_pair(velocity_scale, servo_status);
}
 
double jointLimitVelocityScalingFactor(const Eigen::VectorXd& velocities,
                                       const moveit::core::JointBoundsVector& joint_bounds, double scaling_override)
{
  // If override value is close to zero, user is not overriding the scaling
  double min_scaling_factor = scaling_override;
  if (scaling_override < SCALING_OVERRIDE_THRESHOLD)
  {
    min_scaling_factor = 1.0;  // Set to no scaling override.
  }
 
  // Now get the scaling factor from joint velocity limits.
  size_t idx = 0;
  for (const auto& joint_bound : joint_bounds)
  {
    for (const auto& variable_bound : *joint_bound)
    {
      const auto& target_vel = velocities(idx);
      if (variable_bound.velocity_bounded_ && target_vel != 0.0)
      {
        // Find the ratio of clamped velocity to original velocity
        const auto bounded_vel = std::clamp(target_vel, variable_bound.min_velocity_, variable_bound.max_velocity_);
        const auto joint_scaling_factor = bounded_vel / target_vel;
        min_scaling_factor = std::min(min_scaling_factor, joint_scaling_factor);
      }
      ++idx;
    }
  }
 
  return min_scaling_factor;
}
 
std::vector<int> jointsToHalt(const Eigen::VectorXd& positions, const Eigen::VectorXd& velocities,
                              const moveit::core::JointBoundsVector& joint_bounds, const std::vector<double>& margins)
{
  std::vector<int> joint_idxs_to_halt;
  for (size_t i = 0; i < joint_bounds.size(); i++)
  {
    const auto joint_bound = (joint_bounds[i])->front();
    if (joint_bound.position_bounded_)
    {
      const bool negative_bound = velocities[i] < 0 && positions[i] < (joint_bound.min_position_ + margins[i]);
      const bool positive_bound = velocities[i] > 0 && positions[i] > (joint_bound.max_position_ - margins[i]);
      if (negative_bound || positive_bound)
      {
        joint_idxs_to_halt.push_back(i);
      }
    }
  }
  return joint_idxs_to_halt;
}
 
geometry_msgs::msg::TransformStamped convertIsometryToTransform(const Eigen::Isometry3d& eigen_tf,
                                                                const std::string& parent_frame,
                                                                const std::string& child_frame)
{
  geometry_msgs::msg::TransformStamped output = tf2::eigenToTransform(eigen_tf);
  output.header.frame_id = parent_frame;
  output.child_frame_id = child_frame;
  return output;
}
 
PoseCommand poseFromPoseStamped(const geometry_msgs::msg::PoseStamped& msg)
{
  PoseCommand command;
  command.frame_id = msg.header.frame_id;
 
  const Eigen::Vector3d translation(msg.pose.position.x, msg.pose.position.y, msg.pose.position.z);
  const Eigen::Quaterniond rotation(msg.pose.orientation.w, msg.pose.orientation.x, msg.pose.orientation.y,
                                    msg.pose.orientation.z);
 
  command.pose = Eigen::Isometry3d::Identity();
  command.pose.translate(translation);
  command.pose.linear() = rotation.normalized().toRotationMatrix();
 
  return command;
}
 
planning_scene_monitor::PlanningSceneMonitorPtr createPlanningSceneMonitor(const rclcpp::Node::SharedPtr& node,
                                                                           const servo::Params& servo_params)
{
  // Can set robot_description name from parameters
  std::string robot_description_name = "robot_description";
  node->get_parameter_or("robot_description_name", robot_description_name, robot_description_name);
 
  // Set up planning_scene_monitor
  auto planning_scene_monitor = std::make_shared<planning_scene_monitor::PlanningSceneMonitor>(
      node, robot_description_name, "planning_scene_monitor");
 
  planning_scene_monitor->startStateMonitor(servo_params.joint_topic);
  planning_scene_monitor->startSceneMonitor(servo_params.monitored_planning_scene_topic);
  planning_scene_monitor->startWorldGeometryMonitor(
      planning_scene_monitor::PlanningSceneMonitor::DEFAULT_COLLISION_OBJECT_TOPIC,
      planning_scene_monitor::PlanningSceneMonitor::DEFAULT_PLANNING_SCENE_WORLD_TOPIC,
      servo_params.check_octomap_collisions);
 
  if (servo_params.is_primary_planning_scene_monitor)
  {
    planning_scene_monitor->providePlanningSceneService();
  }
  else
  {
    planning_scene_monitor->requestPlanningSceneState();
  }
 
  planning_scene_monitor->setPlanningScenePublishingFrequency(PLANNING_SCENE_PUBLISHING_FREQUENCY);
  planning_scene_monitor->getStateMonitor()->enableCopyDynamics(true);
  planning_scene_monitor->startPublishingPlanningScene(planning_scene_monitor::PlanningSceneMonitor::UPDATE_SCENE,
                                                       std::string(node->get_fully_qualified_name()) +
                                                           "/publish_planning_scene");
 
  return planning_scene_monitor;
}
 
KinematicState extractRobotState(const moveit::core::RobotStatePtr& robot_state, const std::string& move_group_name)
{
  const moveit::core::JointModelGroup* joint_model_group = robot_state->getJointModelGroup(move_group_name);
  const auto joint_names = joint_model_group->getActiveJointModelNames();
  KinematicState current_state(joint_names.size());
  current_state.joint_names = joint_names;
  robot_state->copyJointGroupPositions(joint_model_group, current_state.positions);
  robot_state->copyJointGroupVelocities(joint_model_group, current_state.velocities);
  robot_state->copyJointGroupAccelerations(joint_model_group, current_state.accelerations);
 
  return current_state;
}
 
}  // namespace moveit_servo