ETA-IK: Execution-Time-Aware Inverse Kinematics for Dual-Arm Systems
Yucheng Tang, Xi Huang, Yongzhou Zhang, Tao Chen, Ilshat Mamaev, Björn Hein
Abstract
This paper presents ETA-IK, a novel Execution-Time-Aware Inverse Kinematics method tailored for dual-arm robotic systems. The primary goal is to optimize motion execution time by leveraging the redundancy of the entire system, specifically in tasks where only the relative pose of the robots is constrained, such as dual-arm scanning of unknown objects. Unlike traditional IK methods using surrogate metrics, our approach directly optimizes execution time while implicitly considering collisions. A neural network based execution time approximator is employed to predict time-efficient joint configurations while accounting for potential collisions. Through experimental evaluation on a system composed of a UR5 and a KUKA iiwa robot, we demonstrate significant reductions in execution time. The proposed method outperforms conventional approaches, showing improved motion efficiency without sacrificing positioning accuracy.
BibTeX
@inproceedings{iros2025_etaikexecutionti,
title = {ETA-IK: Execution-Time-Aware Inverse Kinematics for Dual-Arm Systems},
author = {Yucheng Tang and Xi Huang and Yongzhou Zhang and Tao Chen and Ilshat Mamaev and Björn Hein},
booktitle = {IROS 2025},
year = {2025}
}