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Rapid and Robust Trajectory Optimization for Humanoids

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arxiv 2409.00303 v3 pith:VCU5RA65 submitted 2024-08-31 cs.RO

classification cs.RO
keywords trajectorydesignhumanoidsmethodoptimizationprocessrobustappear
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Performing trajectory design for humanoid robots with high degrees of freedom is computationally challenging. The trajectory design process also often involves carefully selecting various hyperparameters and requires a good initial guess which can further complicate the development process. This work introduces a generalized gait optimization framework that directly generates smooth and physically feasible trajectories. The proposed method demonstrates faster and more robust convergence than existing techniques and explicitly incorporates closed-loop kinematic constraints that appear in many modern humanoids. The method is implemented as an open-source C++ codebase which can be found at https://roahmlab.github.io/RAPTOR/.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Phasing Through the Flames: Rapid Motion Planning with the AGHF PDE for Arbitrary Objective Functions and Constraints

    cs.RO 2025-05 conditional novelty 6.0 of 10

    BLAZE generalizes the Affine Geometric Heat Flow trajectory optimizer to arbitrary cost functions and adds a two-phase scheme that starts from constraint-violating guesses, producing feasible trajectories in seconds f...

  2. Provably-Safe, Online System Identification

    cs.RO 2025-04 conditional novelty 6.0 of 10

    Online, provably safe system identification for a manipulator: safe exciting trajectories plus interval-valued payload estimates refined and used for precise stacking.

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