towr_ros_app.cc

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#include <towr/initialization/gait_generator.h>
#include <towr_ros/towr_ros_interface.h>


namespace towr {

/**
 * @brief An example application of using TOWR together with ROS.
 *
 * Build your own application with your own formulation using the building
 * blocks provided in TOWR and following the example below.
 */
class TowrRosApp : public TowrRosInterface {
public:
  /**
   * @brief Sets the feet to nominal position on flat ground and base above.
   */
  void SetTowrInitialState() override
  {
    auto nominal_stance_B = formulation_.model_.kinematic_model_->GetNominalStanceInBase();

    double z_ground = 0.0;
    formulation_.initial_ee_W_ =  nominal_stance_B;
    std::for_each(formulation_.initial_ee_W_.begin(), formulation_.initial_ee_W_.end(),
                  [&](Vector3d& p){ p.z() = z_ground; } // feet at 0 height
    );

    formulation_.initial_base_.lin.at(kPos).z() = - nominal_stance_B.front().z() + z_ground;
  }

  /**
   * @brief Sets the parameters required to formulate the TOWR problem.
   */
  Parameters GetTowrParameters(int n_ee, const TowrCommandMsg& msg) const override
  {
    Parameters params;

    // Instead of manually defining the initial durations for each foot and
    // step, for convenience we use a GaitGenerator with some predefined gaits
    // for a variety of robots (walk, trot, pace, ...).
    auto gait_gen_ = GaitGenerator::MakeGaitGenerator(n_ee);
    auto id_gait   = static_cast<GaitGenerator::Combos>(msg.gait);
    gait_gen_->SetCombo(id_gait);
    for (int ee=0; ee<n_ee; ++ee) {
      params.ee_phase_durations_.push_back(gait_gen_->GetPhaseDurations(msg.total_duration, ee));
      params.ee_in_contact_at_start_.push_back(gait_gen_->IsInContactAtStart(ee));
    }

    // Here you can also add other constraints or change parameters
    // params.constraints_.push_back(Parameters::BaseRom);

    // increases optimization time, but sometimes helps find a solution for
    // more difficult terrain.
    if (msg.optimize_phase_durations)
      params.OptimizePhaseDurations();

    return params;
  }

  /**
   * @brief Sets the paramters for IPOPT.
   */
  void SetIpoptParameters(const TowrCommandMsg& msg) override
  {
    // the HA-L solvers are alot faster, so consider installing and using
    solver_->SetOption("linear_solver", "mumps"); // ma27, ma57

    // Analytically defining the derivatives in IFOPT as we do it, makes the
    // problem a lot faster. However, if this becomes too difficult, we can also
    // tell IPOPT to just approximate them using finite differences. However,
    // this uses numerical derivatives for ALL constraints, there doesn't yet
    // exist an option to turn on numerical derivatives for only some constraint
    // sets.
    solver_->SetOption("jacobian_approximation", "exact"); // finite difference-values

    // This is a great to test if the analytical derivatives implemented in are
    // correct. Some derivatives that are correct are still flagged, showing a
    // deviation of 10e-4, which is fine. What to watch out for is deviations > 10e-2.
    // solver_->SetOption("derivative_test", "first-order");

    solver_->SetOption("max_cpu_time", 40.0);
    solver_->SetOption("print_level", 5);

    if (msg.play_initialization)
      solver_->SetOption("max_iter", 0);
    else
      solver_->SetOption("max_iter", 3000);
  }
};

} // namespace towr


int main(int argc, char *argv[])
{
  ros::init(argc, argv, "my_towr_ros_app");
  towr::TowrRosApp towr_app;
  ros::spin();

  return 1;
}