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Jerk-limited Real-time Trajectory Generation with Arbitrary Target States

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arxiv 2105.04830 v2 pith:7JRNCYGG submitted 2021-05-11 cs.RO

Lars Berscheid , Torsten Kröger This is my paper · ORCID
classification cs.RO
keywords targetaccelerationalgorithmarbitraryruckigstatestime-optimaltrajectory
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We present Ruckig, an algorithm for Online Trajectory Generation (OTG) respecting third-order constraints and complete kinematic target states. Given any initial state of a system with multiple Degrees of Freedom (DoFs), Ruckig calculates a time-optimal trajectory to an arbitrary target state defined by its position, velocity, and acceleration limited by velocity, acceleration, and jerk constraints. The proposed algorithm and implementation allows three contributions: (1) To the best of our knowledge, we derive the first time-optimal OTG algorithm for arbitrary, multi-dimensional target states, in particular including non-zero target acceleration. (2) This is the first open-source prototype of time-optimal OTG with limited jerk and complete time synchronization for multiple DoFs. (3) Ruckig allows for directional velocity and acceleration limits, enabling robots to better use their dynamical resources. We evaluate the robustness and real-time capability of the proposed algorithm on a test suite with over 1,000,000,000 random trajectories as well as in real-world applications.

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Cited by 5 Pith papers

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  3. SPECTRA: Context-Conditioned Spectral Movement Primitives for Robot Skill Generalization

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  4. GASP: GPU-Accelerated Safe Planner for Real-Time Collision-Aware Motion Generation with Latent Trajectory Sampling

    cs.RO 2026-08 conditional novelty 5.0 of 10

    A learned B-spline planner with latent sampling generates collision-aware joint trajectories on the GPU in near-millisecond time, matching analytical planners and outperforming a GPU optimization baseline.

  5. UTTG_ A Universal Teleoperation Approach via Online Trajectory Generation

    cs.RO 2025-04 conditional novelty 3.0 of 10

    UTTG is a teleoperation framework that reads robot URDF files and applies smoothing-spline interpolation to convert low-rate human commands into high-frequency joint trajectories across three robot platforms.

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