NODE IK: Solving Inverse Kinematics with Neural Ordinary Differential Equations for Path Planning

2022/09/01 by Suhan Park, Park, Suhan, Mathew Schwartz +3 · 2 citations
Computer Science · Engineering · Physics and Astronomy · #FOS: Computer and information sciences #Human Motion and Animation #Human Pose and Action Recognition #Model Reduction and Neural Networks #Robotics (cs.RO)

paper · pdf · doi:10.48550/arxiv.2209.00498

openalex publication_date 2022/09/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper proposes a novel inverse kinematics (IK) solver of articulated robotic systems for path planning. IK is a traditional but essential problem for robot manipulation. Recently, data-driven methods have been proposed to quickly solve the IK for path planning. These methods can handle a large amount of IK requests at once with the advantage of GPUs. However, the accuracy is still low, and the model requires considerable time for training. Therefore, we propose an IK solver that improves accuracy and memory efficiency by utilizing the continuous hidden dynamics of Neural ODE. The performance is compared using multiple robots.

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