Ruckig
Motion Generation for Robots and Machines. Real-time. Jerk-constrained. Time-optimal.
Install / Use
/learn @pantor/RuckigREADME
Ruckig generates trajectories on-the-fly, allowing robots and machines to react instantaneously to sensor input. Ruckig calculates a trajectory to a target waypoint (with position, velocity, and acceleration) starting from any initial state limited by velocity, acceleration, and jerk constraints. Besides the target state, Ruckig allows to define intermediate positions for waypoint following. For state-to-state motions, Ruckig guarantees a time-optimal solution. With intermediate waypoints, Ruckig calculates the path and its time parametrization jointly, resulting in significantly faster trajectories compared to traditional methods.
More information can be found at ruckig.com and in the corresponding paper Jerk-limited Real-time Trajectory Generation with Arbitrary Target States, accepted for the Robotics: Science and Systems (RSS), 2021 conference.
Installation
Ruckig has no dependencies (except for testing). To build Ruckig using CMake, just run
mkdir -p build
cd build
cmake -DCMAKE_BUILD_TYPE=Release ..
make
To install Ruckig in a system-wide directory, you can either use (sudo) make install or install it as debian package using cpack by running
cpack
sudo dpkg -i ruckig*.deb
An example of using Ruckig in your CMake project is given by examples/CMakeLists.txt. However, you can also include Ruckig as a directory within your project and call add_subdirectory(ruckig) in your parent CMakeLists.txt.
Ruckig is also available as a Python module, in particular for development or debugging purposes. The Ruckig Community Version can be installed from PyPI via
pip install ruckig
When using CMake, the Python module can be built using the BUILD_PYTHON_MODULE flag. If you're only interested in the Python module (and not in the C++ library), you can build and install Ruckig via pip install ..
Tutorial
Furthermore, we will explain the basics to get started with online generated trajectories within your application. There is also a collection of examples that guide you through the most important features of Ruckig. A time-optimal trajectory for a single degree of freedom is shown in the figure below. We also added plots of the resulting trajectories for all examples. Let's get started!
Waypoint-based Trajectory Generation
Ruckig provides three main interface classes: the Ruckig, the InputParameter, and the OutputParameter class.
First, you'll need to create a Ruckig instance with the number of DoFs as a template parameter, and the control cycle (e.g. in seconds) in the constructor.
Ruckig<6> ruckig {0.001}; // Number DoFs; control cycle in [s]
The input type has 3 blocks of data: the current state, the target state and the corresponding kinematic limits.
InputParameter<6> input; // Number DoFs
input.current_position = {0.2, ...};
input.current_velocity = {0.1, ...};
input.current_acceleration = {0.1, ...};
input.target_position = {0.5, ...};
input.target_velocity = {-0.1, ...};
input.target_acceleration = {0.2, ...};
input.max_velocity = {0.4, ...};
input.max_acceleration = {1.0, ...};
input.max_jerk = {4.0, ...};
OutputParameter<6> output; // Number DoFs
If you only want to have a acceleration-constrained trajectory, you can also omit the max_jerk as well as the current and target_acceleration value. Given all input and output resources, we can iterate over the trajectory at each discrete time step. For most applications, this loop must run within a real-time thread and controls the actual hardware.
while (ruckig.update(input, output) == Result::Working) {
// Make use of the new state here!
// e.g. robot->setJointPositions(output.new_position);
output.pass_to_input(input); // Don't forget this!
}
Within the control loop, you need to update the current state of the input parameter according to the calculated trajectory. Therefore, the pass_to_input method copies the new kinematic state of the output to the current kinematic state of the input parameter. If (in the next step) the current state is not the expected, pre-calculated trajectory, Ruckig will calculate a new trajectory based on the novel input. When the trajectory has reached the target state, the update function will return Result::Finished.
Intermediate Waypoints
The Ruckig Community Version includes built-in support for intermediate waypoints, using our cloud API for remote calculation. Of course, the Ruckig Pro version is fully local. To allocate the necessary memory for a variable number of waypoints beforehand, we need to pass the maximum number of waypoints to Ruckig via
Ruckig<6> ruckig {0.001, 8};
InputParameter<6> input {8};
OutputParameter<6> output {8};
The InputParameter class takes the number of waypoints as an optional input, however usually you will fill in the values (and therefore reserve its memory) yourself. Then you're ready to set intermediate via points by
input.intermediate_positions = {
{0.2, ...},
{0.8, ...},
};
As soon as at least one intermediate positions is given, the Ruckig Community Version switches to the mentioned (of course, non real-time capable) cloud API. If you require real-time calculation on your own hardware, please contact us for the Ruckig Pro Version.
When using intermediate positions, both the underlying motion planning problem as well as its calculation changes significantly. In particular, there are some fundamental limitations for jerk-limited online trajectory generation regarding the usage of waypoints. Please find more information about these limitations here, and in general we recommend to use
input.intermediate_positions = ruckig.filter_intermediate_positions(input.intermediate_positions, {0.1, ...});
to filter waypoints according to a (high) threshold distance. Setting interrupt_calculation_duration makes sure to be real-time capable by refining the solution in the next control invocation. Note that this is a soft interruption of the calculation. Currently, no minimum or discrete durations are supported when using intermediate positions.
Input Parameter
To go into more detail, the InputParameter type has following members:
using Vector = std::array<double, DOFs>; // By default
Vector current_position;
Vector current_velocity; // Initialized to zero
Vector current_acceleration; // Initialized to zero
std::vector<Vector> intermediate_positions; // (only in Pro Version)
Vector target_position;
Vector target_velocity; // Initialized to zero
Vector target_acceleration; // Initialized to zero
Vector max_velocity;
Vector max_acceleration;
Vector max_jerk; // Initialized to infinity
std::optional<Vector> min_velocity; // If not given, the negative maximum velocity will be used.
std::optional<Vector> min_acceleration; // If not given, the negative maximum acceleration will be used.
std::optional<Vector> min_position; // (only in Pro Version)
std::optional<Vector> max_position; // (only in Pro Version)
std::array<bool, DOFs> enabled; // Initialized to true
std::optional<double> minimum_duration;
std::optional<double> interrupt_calculation_duration; // [µs], (only in Pro Version)
ControlInterface control_interface; // The default position interface controls the full kinematic state.
Synchronization synchronization; // Synchronization behavior of multiple DoFs
DurationDiscretization duration_discretization; // Whether the duration should be a discrete multiple of the control cycle (off by default)
std::optional<Vector<ControlInterface>> per_dof_control_interface; // Sets the control interface for each DoF individually, overwrites global control_interface
std::optional<Vector<Synchronization>> per_dof_synchronization; // Sets the synchronization for each DoF individually, overwrites global synchronization
On top of the current state, target state, and constraints, Ruckig allows for a few more advanced settings:
- A minimum velocity and acceleration can be specified - these should be a negative number. If they are not given, the negative maximum velocity or acceleration will be used (similar to the jerk limit). For example, this might be useful in human robot collaboration settings with a different velocity limit towards a human. Or, when switching between different moving coordinate frames like picking from a conveyer belt.
- You can overwrite the global kinematic limits to specify limits for each section between two waypoints separately by using e.g.
per_section_max_velocity. - If a DoF is not enabled, it will be ignored in the calculation. Ruckig will output a trajectory with constant acceleration for those DoFs.
- A minimum duration can be optionally given. Note that Ruckig can not guarantee an exact, but only a minimum duration of the trajectory.
- The control interface (position or velocity control
