Trajectory optimization package for Mini-Pupper robot

Sotaro Katayama

Last update: Aug 17, 2022

Related tags

Hardware mini-pupper

Overview

Trajectory optimization package for Mini-Pupper robot

Purpose of this repository is to provide low-torque and low-impact trajectory for Mini-Pupper quadrupedal robot.

Requirements

First, install Pinocchio by following the instruction. Next, install robotoc at ROBOTOC_INSTALL_DIR as

git clone https://github.com/mayataka/robotoc & cd robotoc
mkdir build & cd build
cmake .. -DCMAKE_BUILD_TYPE=Release -DOPTIMIZE_FOR_NATIVE=ON -DCMAKE_INSTALL_PREFIX=ROBOTOC_INSTALL_DIR
make install -j4

and modify Python path as

export PYTHONPATH=ROBOTOC_INSTALL_DIR/lib/python3.8/site-packages:$PYTHONPATH

e.g., write it in ~/.bashrc. Finally, install meshcat-python as

pip install meshcat

Running the trajectory optimizer

In mini_pupper_trajopt/trajopt directory, you can run examples of the mini-pupper's gait optimization. You can change the gait parameters such as step length, step height, step timinigs, etc. It visualizes the solution trajectory and save the trajectory.

Deploying the trajectory to the mini-pupper controller

TODO

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Comments

license for this repository

Hi.

What is the license for this repository? I am considering publicly distributing software that has been created by quoting or modifying your software.

Thanks.

opened by nisshan-x 2

step_length is float while in robotoc, step_length is Vector3d

Data type mismatch here

in pacing code, as also trotting and others

class PacingOCPSolverFactory:
    def __init__(self, path_to_urdf=config.PATH_TO_URDF):
        self.path_to_urdf = path_to_urdf 
        self.step_length = 0.02
        self.step_height = 0.03
        # ....

    def create_ocp_solver(self):
       # ....
        LF_foot_ref = robotoc.PeriodicFootTrackRef(x3d_LF, self.step_length, self.step_height, 
                                                   LF_t0, self.swing_time, 
                                                   self.swing_time+2*self.support_time, False)

While in robotoc/bindings/python/robotoc/cost/periodic_foot_track_ref.cpp

PYBIND11_MODULE(periodic_foot_track_ref, m) {
  py::class_<PeriodicFootTrackRef, TimeVaryingTaskSpace3DRefBase,
             std::shared_ptr<PeriodicFootTrackRef>>(m, "PeriodicFootTrackRef")
    .def(py::init<const Eigen::Vector3d&, const Eigen::Vector3d&, const double, 
                  const double, const double, const double, const bool>(),
          py::arg("x3d0"), py::arg("step_length"), py::arg("step_height"),
          py::arg("t0"), py::arg("period_swing"), py::arg("period_stance"),
          py::arg("is_first_step_half"))
    .def("set_foot_track_ref", &PeriodicFootTrackRef::setFootTrackRef,
          py::arg("x3d0"), py::arg("step_length"), py::arg("step_height"),
          py::arg("t0"), py::arg("period_swing"), py::arg("period_stance"),
          py::arg("is_first_step_half")=false)
    .def("update_x3d_ref", &PeriodicFootTrackRef::update_x3d_ref,
          py::arg("grid_info"), py::arg("x3d_ref"))
    .def("is_active", &PeriodicFootTrackRef::isActive,
          py::arg("grid_info"));

examples/anymal/python/pace.py

line 16, step_length = np.array([0.25, 0, 0])

step_length need to be np array

opened by qZhang88 0

Trajectory optimization package for Mini-Pupper robot

Related tags

Overview

Trajectory optimization package for Mini-Pupper robot

Requirements

Running the trajectory optimizer

Deploying the trajectory to the mini-pupper controller

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Comments

license for this repository

step_length is float while in robotoc, step_length is Vector3d

Owner

Sotaro Katayama

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