position_waypoint_motion.hpp

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#pragma once
 
#include <ruckig/ruckig.hpp>
 
#include "franky/motion/reference_type.hpp"
#include "franky/motion/waypoint_motion.hpp"
#include "franky/relative_dynamics_factor.hpp"
#include "franky/util.hpp"
 
namespace franky {
 
template <typename TargetType>
struct PositionWaypoint : public Waypoint<TargetType> {
  ReferenceType reference_type{ReferenceType::kAbsolute};
};
 
template <typename ControlSignalType, typename TargetType>
class PositionWaypointMotion : public WaypointMotion<ControlSignalType, PositionWaypoint<TargetType>, TargetType> {
 public:
  explicit PositionWaypointMotion(
      std::vector<PositionWaypoint<TargetType>> waypoints, const RelativeDynamicsFactor &relative_dynamics_factor = 1.0,
      bool return_when_finished = true)
      : WaypointMotion<ControlSignalType, PositionWaypoint<TargetType>, TargetType>(waypoints, return_when_finished),
        relative_dynamics_factor_(relative_dynamics_factor) {}
 
  [[nodiscard]] const RelativeDynamicsFactor &relative_dynamics_factor() const { return relative_dynamics_factor_; }
 
 protected:
  void setInputLimits(
      const PositionWaypoint<TargetType> &waypoint, ruckig::InputParameter<7> &input_parameter) const override {
    auto [vel_lim, acc_lim, jerk_lim] = getAbsoluteInputLimits();
 
    auto relative_dynamics_factor =
        waypoint.relative_dynamics_factor * relative_dynamics_factor_ * this->robot()->relative_dynamics_factor_rt();
 
    input_parameter.max_velocity = toStdD<7>(relative_dynamics_factor.velocity() * vel_lim);
    input_parameter.max_acceleration = toStdD<7>(relative_dynamics_factor.acceleration() * acc_lim);
    input_parameter.max_jerk = toStdD<7>(relative_dynamics_factor.jerk() * jerk_lim);
 
    if (relative_dynamics_factor.max_dynamics()) {
      input_parameter.synchronization = ruckig::Synchronization::TimeIfNecessary;
    } else {
      input_parameter.synchronization = ruckig::Synchronization::Time;
      if (waypoint.minimum_time.has_value()) input_parameter.minimum_duration = waypoint.minimum_time.value().toSec();
    }
  }
 
  void extrapolateMotion(
      const RobotState &robot_state, const franka::Duration &time_step,
      const ruckig::InputParameter<7> &input_parameter, ruckig::OutputParameter<7> &output_parameter) const override {
    auto [vel_lim, acc_lim, jerk_lim] = getAbsoluteInputLimits();
 
    // We use the desired state here as this is likely what the robot uses
    // internally as well
    auto [pos_d, vel_d, acc_d] = getDesiredState(robot_state);
 
    auto vel = toEigenD<7>(input_parameter.current_velocity);
    auto pos = toEigenD<7>(input_parameter.current_position);
 
    auto vel_delta = acc_d * time_step.toSec();
    auto new_vel_d = (vel_d + vel_delta).cwiseMin(vel_lim).cwiseMax(-vel_lim);
    auto new_pos = pos + (vel_d + new_vel_d) * time_step.toSec() / 2.0;
    auto new_vel = (vel + vel_delta).cwiseMin(vel_lim).cwiseMax(-vel_lim);
 
    // Franka assumes a constant acceleration model if no new input is received.
    // See https://frankaemika.github.io/docs/libfranka.html#under-the-hood
    output_parameter.new_acceleration = input_parameter.current_acceleration;
    output_parameter.new_velocity = toStdD<7>(new_vel);
    output_parameter.new_position = toStdD<7>(new_pos);
  }
 
  [[nodiscard]] std::tuple<Vector7d, Vector7d, Vector7d> getAbsoluteInputLimits() const override = 0;
 
  [[nodiscard]] virtual std::tuple<Vector7d, Vector7d, Vector7d> getDesiredState(
      const RobotState &robot_state) const = 0;
 
 private:
  RelativeDynamicsFactor relative_dynamics_factor_;
};
 
}  // namespace franky