iterative_spline_parameterization.cpp

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/* Author: Ken Anderson */
 
#include <moveit/trajectory_processing/iterative_spline_parameterization.h>
#include <moveit/robot_state/conversions.h>
#include <vector>
 
static const double VLIMIT = 1.0;  // default if not specified in model
static const double ALIMIT = 1.0;  // default if not specified in model
 
namespace trajectory_processing
{
static void fit_cubic_spline(const int n, const double dt[], const double x[], double x1[], double x2[]);
static void adjust_two_positions(const int n, const double dt[], double x[], double x1[], double x2[],
                                 const double x2_i, const double x2_f);
static void init_times(const int n, double dt[], const double x[], const double max_velocity, const double min_velocity);
static double global_adjustment_factor(const int n, double x1[], double x2[], const double max_velocity,
                                       const double min_velocity, const double max_acceleration,
                                       const double min_acceleration);
 
// The path of a single joint: positions, velocities, and accelerations
struct SingleJointTrajectory
{
  std::vector<double> positions_;  // joint's position at time[x]
  std::vector<double> velocities_;
  std::vector<double> accelerations_;
  double initial_acceleration_;
  double final_acceleration_;
  double min_velocity_;
  double max_velocity_;
  double min_acceleration_;
  double max_acceleration_;
};
 
void globalAdjustment(std::vector<SingleJointTrajectory>& t2, int num_joints, const int num_points,
                      std::vector<double>& time_diff);
 
IterativeSplineParameterization::IterativeSplineParameterization(bool add_points) : add_points_(add_points)
{
}
 
bool IterativeSplineParameterization::computeTimeStamps(robot_trajectory::RobotTrajectory& trajectory,
                                                        const double max_velocity_scaling_factor,
                                                        const double max_acceleration_scaling_factor) const
{
  if (trajectory.empty())
    return true;
 
  const moveit::core::JointModelGroup* group = trajectory.getGroup();
  if (!group)
  {
    ROS_ERROR_NAMED("trajectory_processing.iterative_spline_parameterization", "It looks like the planner did not set "
                                                                               "the group the plan was computed for");
    return false;
  }
  const moveit::core::RobotModel& rmodel = group->getParentModel();
  const std::vector<int>& idx = group->getVariableIndexList();
  const std::vector<std::string>& vars = group->getVariableNames();
  double velocity_scaling_factor = 1.0;
  double acceleration_scaling_factor = 1.0;
  unsigned int num_points = trajectory.getWayPointCount();
  unsigned int num_joints = group->getVariableCount();
 
  // Set scaling factors
  if (max_velocity_scaling_factor > 0.0 && max_velocity_scaling_factor <= 1.0)
    velocity_scaling_factor = max_velocity_scaling_factor;
  else if (max_velocity_scaling_factor == 0.0)
    ROS_DEBUG_NAMED("trajectory_processing.iterative_spline_parameterization",
                    "A max_velocity_scaling_factor of 0.0 was specified, defaulting to %f instead.",
                    velocity_scaling_factor);
  else
    ROS_WARN_NAMED("trajectory_processing.iterative_spline_parameterization",
                   "Invalid max_velocity_scaling_factor %f specified, defaulting to %f instead.",
                   max_velocity_scaling_factor, velocity_scaling_factor);
 
  if (max_acceleration_scaling_factor > 0.0 && max_acceleration_scaling_factor <= 1.0)
    acceleration_scaling_factor = max_acceleration_scaling_factor;
  else if (max_acceleration_scaling_factor == 0.0)
    ROS_DEBUG_NAMED("trajectory_processing.iterative_spline_parameterization",
                    "A max_acceleration_scaling_factor of 0.0 was specified, defaulting to %f instead.",
                    acceleration_scaling_factor);
  else
    ROS_WARN_NAMED("trajectory_processing.iterative_spline_parameterization",
                   "Invalid max_acceleration_scaling_factor %f specified, defaulting to %f instead.",
                   max_acceleration_scaling_factor, acceleration_scaling_factor);
 
  // No wrapped angles.
  trajectory.unwind();
 
  if (add_points_)
  {
    // Insert 2nd and 2nd-last points
    // (required to force acceleration to specified values at endpoints)
    if (trajectory.getWayPointCount() >= 2)
    {
      moveit::core::RobotState point = trajectory.getWayPoint(1);
      moveit::core::RobotStatePtr p0, p1;
 
      // 2nd point is 90% of p0, and 10% of p1
      p0 = trajectory.getWayPointPtr(0);
      p1 = trajectory.getWayPointPtr(1);
      for (unsigned int j = 0; j < num_joints; j++)
      {
        point.setVariablePosition(idx[j],
                                  (9 * p0->getVariablePosition(idx[j]) + 1 * p1->getVariablePosition(idx[j])) / 10);
      }
      trajectory.insertWayPoint(1, point, 0.0);
      num_points++;
 
      // 2nd-last point is 10% of p0, and 90% of p1
      p0 = trajectory.getWayPointPtr(num_points - 2);
      p1 = trajectory.getWayPointPtr(num_points - 1);
      for (unsigned int j = 0; j < num_joints; j++)
      {
        point.setVariablePosition(idx[j],
                                  (1 * p0->getVariablePosition(idx[j]) + 9 * p1->getVariablePosition(idx[j])) / 10);
      }
      trajectory.insertWayPoint(num_points - 1, point, 0.0);
      num_points++;
    }
  }
 
  // JointTrajectory indexes in [point][joint] order.
  // We need [joint][point] order to solve efficiently,
  // so convert form here.
 
  std::vector<SingleJointTrajectory> t2(num_joints);
 
  for (unsigned int j = 0; j < num_joints; j++)
  {
    // Copy positions
    t2[j].positions_.resize(num_points, 0.0);
    for (unsigned int i = 0; i < num_points; i++)
    {
      t2[j].positions_[i] = trajectory.getWayPointPtr(i)->getVariablePosition(idx[j]);
    }
 
    // Initialize velocities
    t2[j].velocities_.resize(num_points, 0.0);
    // Copy initial/final velocities if specified
    if (trajectory.getWayPointPtr(0)->hasVelocities())
      t2[j].velocities_[0] = trajectory.getWayPointPtr(0)->getVariableVelocity(idx[j]);
    if (trajectory.getWayPointPtr(num_points - 1)->hasVelocities())
      t2[j].velocities_[num_points - 1] = trajectory.getWayPointPtr(num_points - 1)->getVariableVelocity(idx[j]);
 
    // Initialize accelerations
    t2[j].accelerations_.resize(num_points, 0.0);
    t2[j].initial_acceleration_ = 0.0;
    t2[j].final_acceleration_ = 0.0;
    // Copy initial/final accelerations if specified
    if (trajectory.getWayPointPtr(0)->hasAccelerations())
      t2[j].initial_acceleration_ = trajectory.getWayPointPtr(0)->getVariableAcceleration(idx[j]);
    t2[j].accelerations_[0] = t2[j].initial_acceleration_;
    if (trajectory.getWayPointPtr(num_points - 1)->hasAccelerations())
      t2[j].final_acceleration_ = trajectory.getWayPointPtr(num_points - 1)->getVariableAcceleration(idx[j]);
    t2[j].accelerations_[num_points - 1] = t2[j].final_acceleration_;
 
    // Set bounds based on model, or default limits
    const moveit::core::VariableBounds& bounds = rmodel.getVariableBounds(vars[j]);
    t2[j].max_velocity_ = VLIMIT;
    t2[j].min_velocity_ = -VLIMIT;
    if (bounds.velocity_bounded_)
    {
      t2[j].max_velocity_ = bounds.max_velocity_;
      t2[j].min_velocity_ = bounds.min_velocity_;
      if (t2[j].min_velocity_ == 0.0)
        t2[j].min_velocity_ = -t2[j].max_velocity_;
    }
    t2[j].max_velocity_ *= velocity_scaling_factor;
    t2[j].min_velocity_ *= velocity_scaling_factor;
 
    t2[j].max_acceleration_ = ALIMIT;
    t2[j].min_acceleration_ = -ALIMIT;
    if (bounds.acceleration_bounded_)
    {
      t2[j].max_acceleration_ = bounds.max_acceleration_;
      t2[j].min_acceleration_ = bounds.min_acceleration_;
      if (t2[j].min_acceleration_ == 0.0)
        t2[j].min_acceleration_ = -t2[j].max_acceleration_;
    }
    t2[j].max_acceleration_ *= acceleration_scaling_factor;
    t2[j].min_acceleration_ *= acceleration_scaling_factor;
 
    // Error out if bounds don't make sense
    if (t2[j].max_velocity_ <= 0.0 || t2[j].max_acceleration_ <= 0.0)
    {
      ROS_ERROR_NAMED("trajectory_processing.iterative_spline_parameterization",
                      "Joint %d max velocity %f and max acceleration %f must be greater than zero "
                      "or a solution won't be found.\n",
                      j, t2[j].max_velocity_, t2[j].max_acceleration_);
      return false;
    }
    if (t2[j].min_velocity_ >= 0.0 || t2[j].min_acceleration_ >= 0.0)
    {
      ROS_ERROR_NAMED("trajectory_processing.iterative_spline_parameterization",
                      "Joint %d min velocity %f and min acceleration %f must be less than zero "
                      "or a solution won't be found.\n",
                      j, t2[j].min_velocity_, t2[j].min_acceleration_);
      return false;
    }
  }
 
  // Error check
  if (num_points < 4)
  {
    ROS_ERROR_NAMED("trajectory_processing.iterative_spline_parameterization",
                    "number of waypoints %d, needs to be greater than 3.\n", num_points);
    return false;
  }
  for (unsigned int j = 0; j < num_joints; j++)
  {
    if (t2[j].velocities_[0] > t2[j].max_velocity_ || t2[j].velocities_[0] < t2[j].min_velocity_)
    {
      ROS_ERROR_NAMED("trajectory_processing.iterative_spline_parameterization", "Initial velocity %f out of bounds\n",
                      t2[j].velocities_[0]);
      return false;
    }
    else if (t2[j].velocities_[num_points - 1] > t2[j].max_velocity_ ||
             t2[j].velocities_[num_points - 1] < t2[j].min_velocity_)
    {
      ROS_ERROR_NAMED("trajectory_processing.iterative_spline_parameterization", "Final velocity %f out of bounds\n",
                      t2[j].velocities_[num_points - 1]);
      return false;
    }
    else if (t2[j].accelerations_[0] > t2[j].max_acceleration_ || t2[j].accelerations_[0] < t2[j].min_acceleration_)
    {
      ROS_ERROR_NAMED("trajectory_processing.iterative_spline_parameterization",
                      "Initial acceleration %f out of bounds\n", t2[j].accelerations_[0]);
      return false;
    }
    else if (t2[j].accelerations_[num_points - 1] > t2[j].max_acceleration_ ||
             t2[j].accelerations_[num_points - 1] < t2[j].min_acceleration_)
    {
      ROS_ERROR_NAMED("trajectory_processing.iterative_spline_parameterization",
                      "Final acceleration %f out of bounds\n", t2[j].accelerations_[num_points - 1]);
      return false;
    }
  }
 
  // Initialize times
  // start with valid velocities, then expand intervals
  // epsilon to prevent divide-by-zero
  std::vector<double> time_diff(trajectory.getWayPointCount() - 1, std::numeric_limits<double>::epsilon());
  for (unsigned int j = 0; j < num_joints; j++)
    init_times(num_points, &time_diff[0], &t2[j].positions_[0], t2[j].max_velocity_, t2[j].min_velocity_);
 
  // Stretch intervals until close to the bounds
  while (1)
  {
    int loop = 0;
 
    // Calculate the interval stretches due to acceleration
    std::vector<double> time_factor(num_points - 1, 1.00);
    for (unsigned j = 0; j < num_joints; j++)
    {
      // Move points to satisfy initial/final acceleration
      if (add_points_)
      {
        adjust_two_positions(num_points, &time_diff[0], &t2[j].positions_[0], &t2[j].velocities_[0],
                             &t2[j].accelerations_[0], t2[j].initial_acceleration_, t2[j].final_acceleration_);
      }
 
      fit_cubic_spline(num_points, &time_diff[0], &t2[j].positions_[0], &t2[j].velocities_[0], &t2[j].accelerations_[0]);
      for (unsigned i = 0; i < num_points; i++)
      {
        const double acc = t2[j].accelerations_[i];
        double atfactor = 1.0;
        if (acc > t2[j].max_acceleration_)
          atfactor = sqrt(acc / t2[j].max_acceleration_);
        if (acc < t2[j].min_acceleration_)
          atfactor = sqrt(acc / t2[j].min_acceleration_);
        if (atfactor > 1.01)  // within 1%
          loop = 1;
        atfactor = (atfactor - 1.0) / 16.0 + 1.0;  // 1/16th
        if (i > 0)
          time_factor[i - 1] = std::max(time_factor[i - 1], atfactor);
        if (i < num_points - 1)
          time_factor[i] = std::max(time_factor[i], atfactor);
      }
    }
 
    if (loop == 0)
      break;  // finished
 
    // Stretch
    for (unsigned i = 0; i < num_points - 1; i++)
      time_diff[i] *= time_factor[i];
  }
 
  // Final adjustment forces the trajectory within bounds
  globalAdjustment(t2, num_joints, num_points, time_diff);
 
  // Convert back to JointTrajectory form
  for (unsigned int i = 1; i < num_points; i++)
    trajectory.setWayPointDurationFromPrevious(i, time_diff[i - 1]);
  for (unsigned int i = 0; i < num_points; i++)
  {
    for (unsigned int j = 0; j < num_joints; j++)
    {
      trajectory.getWayPointPtr(i)->setVariableVelocity(idx[j], t2[j].velocities_[i]);
      trajectory.getWayPointPtr(i)->setVariableAcceleration(idx[j], t2[j].accelerations_[i]);
    }
 
    // Only update position of additionally inserted points (at second and next-to-last position)
    if (add_points_ && (i == 1 || i == num_points - 2))
    {
      for (unsigned int j = 0; j < num_joints; j++)
        trajectory.getWayPointPtr(i)->setVariablePosition(idx[j], t2[j].positions_[i]);
      trajectory.getWayPointPtr(i)->update();
    }
  }
 
  return true;
}
 
 
/*
  Fit a 'clamped' cubic spline over a series of points.
  A cubic spline ensures continuous function across positions,
  1st derivative (velocities), and 2nd derivative (accelerations).
  'Clamped' means the first derivative at the endpoints is specified.
 
  Fitting a cubic spline involves solving a series of linear equations.
  The general form for each segment is:
    (tj-t_(j-1))*x"_(j-1) + 2*(t_(j+1)-t_(j-1))*x"j + (t_(j+1)-tj)*x"_j+1) =
          (x_(j+1)-xj)/(t_(j+1)-tj) - (xj-x_(j-1))/(tj-t_(j-1))
  And the first and last segment equations are clamped to specified values: x1_i and x1_f.
 
  Represented in matrix form:
  [ 2*(t1-t0)   (t1-t0)                              0              ][x0"]       [(x1-x0)/(t1-t0) - t1_i           ]
  [ t1-t0       2*(t2-t0)   t2-t1                                   ][x1"]       [(x2-x1)/(t2-t1) - (x1-x0)/(t1-t0)]
  [             t2-t1       2*(t3-t1)   t3-t2                       ][x2"] = 6 * [(x3-x2)/(t3/t2) - (x2-x1)/(t2-t1)]
  [                       ...         ...         ...               ][...]       [...                              ]
  [ 0                                    tN-t_(N-1)  2*(tN-t_(N-1)) ][xN"]       [t1_f - (xN-x_(N-1))/(tN-t_(N-1)) ]
 
  This matrix is tridiagonal, which can be solved solved in O(N) time
  using the tridiagonal algorithm.
  There is a forward propogation pass followed by a backsubstitution pass.
 
  n is the number of points
  dt contains the time difference between each point (size=n-1)
  x  contains the positions                          (size=n)
  x1 contains the 1st derivative (velocities)        (size=n)
     x1[0] and x1[n-1] MUST be specified.
  x2 contains the 2nd derivative (accelerations)     (size=n)
  x1 and x2 are filled in by the algorithm.
*/
 
static void fit_cubic_spline(const int n, const double dt[], const double x[], double x1[], double x2[])
{
  int i;
  const double x1_i = x1[0], x1_f = x1[n - 1];
 
  // Tridiagonal alg - forward sweep
  // x1 and x2 used to store the temporary coefficients c and d
  // (will get overwritten during backsubstitution)
  double *c = x1, *d = x2;
  c[0] = 0.5;
  d[0] = 3.0 * ((x[1] - x[0]) / dt[0] - x1_i) / dt[0];
  for (i = 1; i <= n - 2; i++)
  {
    const double dt2 = dt[i - 1] + dt[i];
    const double a = dt[i - 1] / dt2;
    const double denom = 2.0 - a * c[i - 1];
    c[i] = (1.0 - a) / denom;
    d[i] = 6.0 * ((x[i + 1] - x[i]) / dt[i] - (x[i] - x[i - 1]) / dt[i - 1]) / dt2;
    d[i] = (d[i] - a * d[i - 1]) / denom;
  }
  const double denom = dt[n - 2] * (2.0 - c[n - 2]);
  d[n - 1] = 6.0 * (x1_f - (x[n - 1] - x[n - 2]) / dt[n - 2]);
  d[n - 1] = (d[n - 1] - dt[n - 2] * d[n - 2]) / denom;
 
  // Tridiagonal alg - backsubstitution sweep
  // 2nd derivative
  x2[n - 1] = d[n - 1];
  for (i = n - 2; i >= 0; i--)
    x2[i] = d[i] - c[i] * x2[i + 1];
 
  // 1st derivative
  x1[0] = x1_i;
  for (i = 1; i < n - 1; i++)
    x1[i] = (x[i + 1] - x[i]) / dt[i] - (2 * x2[i] + x2[i + 1]) * dt[i] / 6.0;
  x1[n - 1] = x1_f;
}
 
/*
  Modify the value of x[1] and x[N-2]
  so that 2nd derivative starts and ends at specified value.
  This involves fitting the spline twice,
  then solving for the specified value.
 
  x2_i and x2_f are the (initial and final) 2nd derivative at 0 and N-1
*/
 
static void adjust_two_positions(const int n, const double dt[], double x[], double x1[], double x2[],
                                 const double x2_i, const double x2_f)
{
  x[1] = x[0];
  x[n - 2] = x[n - 3];
  fit_cubic_spline(n, dt, x, x1, x2);
  double a0 = x2[0];
  double b0 = x2[n - 1];
 
  x[1] = x[2];
  x[n - 2] = x[n - 1];
  fit_cubic_spline(n, dt, x, x1, x2);
  double a2 = x2[0];
  double b2 = x2[n - 1];
 
  // we can solve this with linear equation (use two-point form)
  if (a2 != a0)
    x[1] = x[0] + ((x[2] - x[0]) / (a2 - a0)) * (x2_i - a0);
  if (b2 != b0)
    x[n - 2] = x[n - 3] + ((x[n - 1] - x[n - 3]) / (b2 - b0)) * (x2_f - b0);
}
 
/*
  Find time required to go max velocity on each segment.
  Increase a segment's time interval if the current time isn't long enough.
*/
 
static void init_times(const int n, double dt[], const double x[], const double max_velocity, const double min_velocity)
{
  int i;
  for (i = 0; i < n - 1; i++)
  {
    double time;
    double dx = x[i + 1] - x[i];
    if (dx >= 0.0)
      time = (dx / max_velocity);
    else
      time = (dx / min_velocity);
    time += std::numeric_limits<double>::epsilon();  // prevent divide-by-zero
 
    if (dt[i] < time)
      dt[i] = time;
  }
}
 
#if 0  // unused function
/*
  Fit a spline, then check each interval to see if bounds are met.
  If all bounds met (no time adjustments made), return 0.
  If bounds not met (time adjustments made), slightly increase the
  surrounding time intervals and return 1.
 
  n is the number of points
  dt contains the time difference between each point (size=n-1)
  x  contains the positions                          (size=n)
  x1 contains the 1st derivative (velocities)        (size=n)
     x1[0] and x1[n-1] MUST be specified.
  x2 contains the 2nd derivative (accelerations)     (size=n)
  max_velocity is the max velocity for this joint.
  min_velocity is the min velocity for this joint.
  max_acceleration is the max acceleration for this joint.
  min_acceleration is the min acceleration for this joint.
  tfactor is the time adjustment (multiplication) factor.
  x1 and x2 are filled in by the algorithm.
*/
 
static int fit_spline_and_adjust_times(const int n, double dt[], const double x[], double x1[], double x2[],
                                       const double max_velocity, const double min_velocity,
                                       const double max_acceleration, const double min_acceleration,
                                       const double tfactor)
{
  int i, ret = 0;
 
  fit_cubic_spline(n, dt, x, x1, x2);
 
  // Instantaneous velocity is calculated at each point
  for (i = 0; i < n - 1; i++)
  {
    const double vel = x1[i];
    const double vel2 = x1[i + 1];
    if (vel > max_velocity || vel < min_velocity || vel2 > max_velocity || vel2 < min_velocity)
    {
      dt[i] *= tfactor;
      ret = 1;
    }
  }
  // Instantaneous acceleration is calculated at each point
  if (ret == 0)
  {
    for (i = 0; i < n - 1; i++)
    {
      const double acc = x2[i];
      const double acc2 = x2[i + 1];
      if (acc > max_acceleration || acc < min_acceleration || acc2 > max_acceleration || acc2 < min_acceleration)
      {
        dt[i] *= tfactor;
        ret = 1;
      }
    }
  }
 
  return ret;
}
#endif
 
// return global expansion multiplicative factor required
// to force within bounds.
// Assumes that the spline is already fit
// (fit_cubic_spline must have been called before this).
static double global_adjustment_factor(const int n, double x1[], double x2[], const double max_velocity,
                                       const double min_velocity, const double max_acceleration,
                                       const double min_acceleration)
{
  int i;
  double tfactor2 = 1.00;
 
  for (i = 0; i < n; i++)
  {
    double tfactor;
    tfactor = x1[i] / max_velocity;
    if (tfactor2 < tfactor)
      tfactor2 = tfactor;
    tfactor = x1[i] / min_velocity;
    if (tfactor2 < tfactor)
      tfactor2 = tfactor;
 
    if (x2[i] >= 0)
    {
      tfactor = sqrt(fabs(x2[i] / max_acceleration));
      if (tfactor2 < tfactor)
        tfactor2 = tfactor;
    }
    else
    {
      tfactor = sqrt(fabs(x2[i] / min_acceleration));
      if (tfactor2 < tfactor)
        tfactor2 = tfactor;
    }
  }
 
  return tfactor2;
}
 
// Expands the entire trajectory to fit exactly within bounds
void globalAdjustment(std::vector<SingleJointTrajectory>& t2, int num_joints, const int num_points,
                      std::vector<double>& time_diff)
{
  double gtfactor = 1.0;
  for (int j = 0; j < num_joints; j++)
  {
    double tfactor;
    tfactor = global_adjustment_factor(num_points, &t2[j].velocities_[0], &t2[j].accelerations_[0], t2[j].max_velocity_,
                                       t2[j].min_velocity_, t2[j].max_acceleration_, t2[j].min_acceleration_);
    if (tfactor > gtfactor)
      gtfactor = tfactor;
  }
 
  // printf("# Global adjustment: %0.4f%%\n", 100.0 * (gtfactor - 1.0));
  for (int i = 0; i < num_points - 1; i++)
    time_diff[i] *= gtfactor;
 
  for (int j = 0; j < num_joints; j++)
  {
    fit_cubic_spline(num_points, &time_diff[0], &t2[j].positions_[0], &t2[j].velocities_[0], &t2[j].accelerations_[0]);
  }
}
}  // namespace trajectory_processing