Ruckig 0.17.1
Motion Generation for Robots and Machines
 
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(12) Custom Vector Type
  • C++
    #include "plotter.hpp"
    template<class T, size_t DOFs>
    class MinimalVector {
    T data[DOFs];
    public:
    MinimalVector() { }
    MinimalVector(std::initializer_list<T> a) {
    std::copy_n(a.begin(), DOFs, std::begin(data));
    }
    T operator[](size_t i) const {
    return data[i];
    }
    T& operator[](size_t i) {
    return data[i];
    }
    size_t size() const {
    return DOFs;
    }
    bool operator==(const MinimalVector<T, DOFs>& rhs) const {
    for (size_t dof = 0; dof < DOFs; ++dof) {
    if (data[dof] != rhs[dof]) {
    return false;
    }
    }
    return true;
    }
    };
    using namespace ruckig;
    int main() {
    // Create instances: the Ruckig trajectory generator as well as input and output parameters
    Ruckig<3, MinimalVector> ruckig(0.01); // control cycle
    // Set input parameters
    input.current_position = {0.0, 0.0, 0.5};
    input.current_velocity = {0.0, -2.2, -0.5};
    input.current_acceleration = {0.0, 2.5, -0.5};
    input.target_position = {5.0, -2.0, -3.5};
    input.target_velocity = {0.0, -0.5, -2.0};
    input.target_acceleration = {0.0, 0.0, 0.5};
    input.max_velocity = {3.0, 1.0, 3.0};
    input.max_acceleration = {3.0, 2.0, 1.0};
    input.max_jerk = {4.0, 3.0, 2.0};
    // Generate the trajectory within the control loop
    std::cout << "t | position" << std::endl;
    while (ruckig.update(input, output) == Result::Working) {
    std::cout << output.time << " | " << pretty_print(output.new_position) << std::endl;
    output.pass_to_input(input);
    }
    std::cout << "Trajectory duration: " << output.trajectory.get_duration() << " [s]." << std::endl;
    }
    Main interface for the Ruckig algorithm.
    Definition ruckig.hpp:27
    Definition block.hpp:16
  • Python
    # ---
    #
    # Nothing to see here, as the custom vector types don't affect the Python version.
    #
    # ---

Output Trajectory