Motion Generation for Robots and Machines
The core Ruckig algorithm calculates a trajectory to a target state (with position, velocity, and acceleration) starting from any initial state limited by velocity, acceleration, and jerk constraints. This calculation is done within the real-time control loop of the robot or machine, enabling it to instantaneously react to sensor input and replan its motion accordingly. Moreover, Ruckig allows for obstacle environments or intermediate waypoints to calculate complex trajectories on-the-fly, even surpassing offline approaches for motion planning in terms of trajectory duration. Ruckig is the first trajectory generator for arbitrary target states and supports directional velocity and acceleration limits, minimum trajectory durations, and many more features.
RuckigCommunity Version |
RuckigPro Version |
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Arbitrary initial and target states
given by position, velocity, and acceleration |
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Jerk limitation
on top of velocity and acceleration constraints |
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Velocity control interface
easily switch to velocity control, e.g. to safely stop the robot |
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Time synchronization of multiple axes
reach the target state simultaneously / in straight-line motions |
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Hard real-time capability
for guaranteed performance in critical environments |
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Increased reliability
numerical robustness for the most demanding applications |
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Position limitation
to restrict the workspace of the system |
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Intermediate waypoints
for time-optimized trajectories |
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Tracking
to closely follow a moving signal with kinematic constraints |
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| Support & integration | ||
| Codebase | ≥ C++20 ≥ Python 3.10 | ≥ C++03 ≥ Python 3.8 |
| Software license | Open Source (MIT) | Individual 30-day trial |
| GitHub | Request Evaluation | |
| Documentation | ||
Ruckig powers pick-and-place, welding, assembly, bin-picking, and jogging tasks with time-optimal trajectories that reduce cycle times.
From cobots to humanoids, Ruckig provides safe and smooth motion execution for VLA (Vision-Language-Action) models and teleoperation systems.
When robots must react to vision input in real-time, Ruckig bridges the gap between perception and actuation, e.g. for camera-based control, conveyor tracking, or collision avoidance.
Ruckig optimizes toolpath execution with time-optimal trajectories while respecting machine constraints for improved surface finish and reduced cycle times.
From ground vehicles to flight control, Ruckig's online trajectory generation enables instantaneous replanning when obstacles appear or targets move.
Even on resource-constrained hardware and microcontrollers, Ruckig controls motor drives with precise velocity, acceleration, and jerk limits.
Ruckig integrates into IEC 62304-compliant software architectures for medical robots, with full lifecycle documentation, traceability, and test coverage.
For laser cutting, welding, and marking, Ruckig generates precise scanning trajectories with control rates exceeding 50kHz for exact energy deposition.
Ruckig already controls container cranes, wired cameras in sports arenas, and instruments for minimally invasive surgeries. What about yours?
Ruckig is developed by Griffig Robotics GmbH, a company founded and led by Lars Berscheid. The algorithm originates from his research at the Karlsruhe Institute of Technology (KIT), where he developed the first method for computing time-optimal, jerk-limited motions to arbitrary target states, published as "Jerk-limited real-time trajectory generation for arbitrary target states" at Robotics: Science and Systems (RSS) 2021. He subsequently continued his research at the University of California, Berkeley.
Since publication, the Ruckig Pro version has been integrated into production systems across multiple industries worldwide. Griffig Robotics provides consulting, integration, and long-term support for professional deployments.
We're happy to answer your questions and discuss how Ruckig can help you.
Send us a short note about your application, and we'll set you up with an evaluation license.
or write us an email at hello@ruckig.com
